CINXE.COM

<!DOCTYPE html> <html lang="en" dir="ltr"> <head>  <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script>  <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript>    <title>Search results for: model parameters identification</title> <meta name="description" content="Search results for: model parameters identification"> <meta name="keywords" content="model parameters identification"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="model parameters identification" name="q" aria-label="Search"> <button class="btn btn-light my-2 my-sm-0" type="submit"><i class="fas fa-search"></i></button> </form> </div> <div class="collapse navbar-collapse mt-1" id="navbarMenu"> <ul class="navbar-nav ml-auto align-items-center" id="mainNavMenu"> <li class="nav-item"> <a class="nav-link" href="https://waset.org/conferences" title="Conferences in 2024/2025/2026">Conferences</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/disciplines" title="Disciplines">Disciplines</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/committees" rel="nofollow">Committees</a> </li> <li class="nav-item dropdown"> <a class="nav-link dropdown-toggle" href="#" id="navbarDropdownPublications" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> Publications </a> <div class="dropdown-menu" aria-labelledby="navbarDropdownPublications"> <a class="dropdown-item" href="https://publications.waset.org/abstracts">Abstracts</a> <a class="dropdown-item" href="https://publications.waset.org">Periodicals</a> <a class="dropdown-item" href="https://publications.waset.org/archive">Archive</a> </div> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/page/support" title="Support">Support</a> </li> </ul> </div> </div> </nav> </div> </header> <main> <div class="container mt-4"> <div class="row"> <div class="col-md-9 mx-auto"> <form method="get" action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="model parameters identification"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 25057</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: model parameters identification</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25057</span> Parameters Estimation of Multidimensional Possibility Distributions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sergey%20Sorokin">Sergey Sorokin</a>, <a href="https://publications.waset.org/abstracts/search?q=Irina%20Sorokina"> Irina Sorokina</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexander%20Yazenin"> Alexander Yazenin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We present a solution to the Maxmin u/E parameters estimation problem of possibility distributions in m-dimensional case. Our method is based on geometrical approach, where minimal area enclosing ellipsoid is constructed around the sample. Also we demonstrate that one can improve results of well-known algorithms in fuzzy model identification task using Maxmin u/E parameters estimation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=possibility%20distribution" title="possibility distribution">possibility distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=parameters%20estimation" title=" parameters estimation"> parameters estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=Maxmin%20u%5CE%20estimator" title=" Maxmin u\E estimator"> Maxmin u\E estimator</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20model%20identification" title=" fuzzy model identification"> fuzzy model identification</a> </p> <a href="https://publications.waset.org/abstracts/16751/parameters-estimation-of-multidimensional-possibility-distributions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16751.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">470</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25056</span> Parameters Identification and Sensitivity Study for Abrasive WaterJet Milling Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Didier%20Auroux">Didier Auroux</a>, <a href="https://publications.waset.org/abstracts/search?q=Vladimir%20Groza"> Vladimir Groza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abrasive%20Waterjet%20Milling" title="Abrasive Waterjet Milling">Abrasive Waterjet Milling</a>, <a href="https://publications.waset.org/abstracts/search?q=inverse%20problem" title=" inverse problem"> inverse problem</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification" title=" model parameters identification"> model parameters identification</a>, <a href="https://publications.waset.org/abstracts/search?q=regularization" title=" regularization"> regularization</a> </p> <a href="https://publications.waset.org/abstracts/46293/parameters-identification-and-sensitivity-study-for-abrasive-waterjet-milling-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46293.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">316</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25055</span> Genetic Algorithms for Parameter Identification of DC Motor ARMAX Model and Optimal Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Mansouri">A. Mansouri</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Krim"> F. Krim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents two techniques for DC motor parameters identification. We propose a numerical method using the adaptive extensive recursive least squares (AERLS) algorithm for real time parameters estimation. This algorithm, based on minimization of quadratic criterion, is realized in simulation for parameters identification of DC motor autoregressive moving average with extra inputs (ARMAX). As advanced technique, we use genetic algorithms (GA) identification with biased estimation for high dynamic performance speed regulation. DC motors are extensively used in variable speed drives, for robot and solar panel trajectory control. GA effectiveness is derived through comparison of the two approaches. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ARMAX%20model" title="ARMAX model">ARMAX model</a>, <a href="https://publications.waset.org/abstracts/search?q=DC%20motor" title=" DC motor"> DC motor</a>, <a href="https://publications.waset.org/abstracts/search?q=AERLS" title=" AERLS"> AERLS</a>, <a href="https://publications.waset.org/abstracts/search?q=GA" title=" GA"> GA</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20identification" title=" parameter identification"> parameter identification</a>, <a href="https://publications.waset.org/abstracts/search?q=PID%20speed%20regulation" title=" PID speed regulation"> PID speed regulation</a> </p> <a href="https://publications.waset.org/abstracts/9107/genetic-algorithms-for-parameter-identification-of-dc-motor-armax-model-and-optimal-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9107.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">380</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25054</span> Estimation of Structural Parameters in Time Domain Using One Dimensional Piezo Zirconium Titanium Patch Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Jinesh">N. Jinesh</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Shankar"> K. Shankar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=inverse%20problem" title="inverse problem">inverse problem</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title=" particle swarm optimization"> particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=PZT%20patches" title=" PZT patches"> PZT patches</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20identification" title=" structural identification"> structural identification</a> </p> <a href="https://publications.waset.org/abstracts/54524/estimation-of-structural-parameters-in-time-domain-using-one-dimensional-piezo-zirconium-titanium-patch-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54524.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">309</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25053</span> Identification of Dynamic Friction Model for High-Precision Motion Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Martin%20Goubej">Martin Goubej</a>, <a href="https://publications.waset.org/abstracts/search?q=Tomas%20Popule"> Tomas Popule</a>, <a href="https://publications.waset.org/abstracts/search?q=Alois%20Krejci"> Alois Krejci</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper deals with experimental identification of mechanical systems with nonlinear friction characteristics. Dynamic LuGre friction model is adopted and a systematic approach to parameter identification of both linear and nonlinear subsystems is given. The identification procedure consists of three subsequent experiments which deal with the individual parts of plant dynamics. The proposed method is experimentally verified on an industrial-grade robotic manipulator. Model fidelity is compared with the results achieved with a static friction model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mechanical%20friction" title="mechanical friction">mechanical friction</a>, <a href="https://publications.waset.org/abstracts/search?q=LuGre%20model" title=" LuGre model"> LuGre model</a>, <a href="https://publications.waset.org/abstracts/search?q=friction%20identification" title=" friction identification"> friction identification</a>, <a href="https://publications.waset.org/abstracts/search?q=motion%20control" title=" motion control"> motion control</a> </p> <a href="https://publications.waset.org/abstracts/51897/identification-of-dynamic-friction-model-for-high-precision-motion-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51897.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">413</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25052</span> Adaptive Kaman Filter for Fault Diagnosis of Linear Parameter-Varying Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rajamani%20Doraiswami">Rajamani Doraiswami</a>, <a href="https://publications.waset.org/abstracts/search?q=Lahouari%20Cheded"> Lahouari Cheded</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=identification" title="identification">identification</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20parameter-varying%20systems" title=" linear parameter-varying systems"> linear parameter-varying systems</a>, <a href="https://publications.waset.org/abstracts/search?q=least-squares%20estimation" title=" least-squares estimation"> least-squares estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=fault%20diagnosis" title=" fault diagnosis"> fault diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=emulators" title=" emulators"> emulators</a> </p> <a href="https://publications.waset.org/abstracts/7656/adaptive-kaman-filter-for-fault-diagnosis-of-linear-parameter-varying-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7656.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">499</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25051</span> Influence of Optimization Method on Parameters Identification of Hyperelastic Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bale%20Baidi%20Blaise">Bale Baidi Blaise</a>, <a href="https://publications.waset.org/abstracts/search?q=Gilles%20Marckmann"> Gilles Marckmann</a>, <a href="https://publications.waset.org/abstracts/search?q=Liman%20%20Kaoye"> Liman Kaoye</a>, <a href="https://publications.waset.org/abstracts/search?q=Talaka%20Dya"> Talaka Dya</a>, <a href="https://publications.waset.org/abstracts/search?q=Moustapha%20Bachirou"> Moustapha Bachirou</a>, <a href="https://publications.waset.org/abstracts/search?q=Gambo%20Betchewe"> Gambo Betchewe</a>, <a href="https://publications.waset.org/abstracts/search?q=Tibi%20Beda"> Tibi Beda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work highlights the capabilities of particles swarm optimization (PSO) method to identify parameters of hyperelastic models. The study compares this method with Genetic Algorithm (GA) method, Least Squares (LS) method, Pattern Search Algorithm (PSA) method, Beda-Chevalier (BC) method and the Levenberg-Marquardt (LM) method. Four classic hyperelastic models are used to test the diﬀerent methods through parameters identification. Then, the study compares the ability of these models to reproduce experimental Treloar data in simple tension, biaxial tension and pure shear. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization" title="particle swarm optimization">particle swarm optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=identification" title=" identification"> identification</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperelastic" title=" hyperelastic"> hyperelastic</a>, <a href="https://publications.waset.org/abstracts/search?q=model" title=" model"> model</a> </p> <a href="https://publications.waset.org/abstracts/138255/influence-of-optimization-method-on-parameters-identification-of-hyperelastic-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/138255.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">171</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25050</span> Analytical and Statistical Study of the Parameters of Expansive Soil</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Medjnoun">A. Medjnoun</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Bahar"> R. Bahar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The disorders caused by the shrinking-swelling phenomenon are prevalent in arid and semi-arid in the presence of swelling clay. This soil has the characteristic of changing state under the effect of water solicitation (wetting and drying). A set of geotechnical parameters is necessary for the characterization of this soil type, such as state parameters, physical and chemical parameters and mechanical parameters. Some of these tests are very long and some are very expensive, hence the use or methods of predictions. The complexity of this phenomenon and the difficulty of its characterization have prompted researchers to use several identification parameters in the prediction of swelling potential. This document is an analytical and statistical study of geotechnical parameters affecting the potential of swelling clays. This work is performing on a database obtained from investigations swelling Algerian soil. The obtained observations have helped us to understand the soil swelling structure and its behavior. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analysis" title="analysis">analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=estimated%20model" title=" estimated model"> estimated model</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20identification" title=" parameter identification"> parameter identification</a>, <a href="https://publications.waset.org/abstracts/search?q=swelling%20of%20clay" title=" swelling of clay"> swelling of clay</a> </p> <a href="https://publications.waset.org/abstracts/37170/analytical-and-statistical-study-of-the-parameters-of-expansive-soil" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37170.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">417</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25049</span> Material Parameter Identification of Modified AbdelKarim-Ohno Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Martin%20Cermak">Martin Cermak</a>, <a href="https://publications.waset.org/abstracts/search?q=Tomas%20Karasek"> Tomas Karasek</a>, <a href="https://publications.waset.org/abstracts/search?q=Jaroslav%20Rojicek"> Jaroslav Rojicek</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The key role in phenomenological modelling of cyclic plasticity is good understanding of stress-strain behaviour of given material. There are many models describing behaviour of materials using numerous parameters and constants. Combination of individual parameters in those material models significantly determines whether observed and predicted results are in compliance. Parameter identification techniques such as random gradient, genetic algorithm, and sensitivity analysis are used for identification of parameters using numerical modelling and simulation. In this paper genetic algorithm and sensitivity analysis are used to study effect of 4 parameters of modified AbdelKarim-Ohno cyclic plasticity model. Results predicted by Finite Element (FE) simulation are compared with experimental data from biaxial ratcheting test with semi-elliptical loading path. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title="genetic algorithm">genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=sensitivity%20analysis" title=" sensitivity analysis"> sensitivity analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=inverse%20approach" title=" inverse approach"> inverse approach</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20element%20method" title=" finite element method"> finite element method</a>, <a href="https://publications.waset.org/abstracts/search?q=cyclic%20plasticity" title=" cyclic plasticity"> cyclic plasticity</a>, <a href="https://publications.waset.org/abstracts/search?q=ratcheting" title=" ratcheting "> ratcheting </a> </p> <a href="https://publications.waset.org/abstracts/21152/material-parameter-identification-of-modified-abdelkarim-ohno-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21152.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">453</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25048</span> An Optimal Approach for Full-Detailed Friction Model Identification of Reaction Wheel</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ghasem%20Sharifi">Ghasem Sharifi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamed%20Shahmohamadi%20Ousaloo"> Hamed Shahmohamadi Ousaloo</a>, <a href="https://publications.waset.org/abstracts/search?q=Milad%20Azimi"> Milad Azimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mehran%20Mirshams"> Mehran Mirshams</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The ever-increasing use of satellites demands a search for increasingly accurate and reliable pointing systems. Reaction wheels are rotating devices used commonly for the attitude control of the spacecraft since provide a wide range of torque magnitude and high reliability. The numerical modeling of this device can significantly enhance the accuracy of the satellite control in space. Modeling the wheel rotation in the presence of the various frictions is one of the critical parts of this approach. This paper presents a Dynamic Model Control of a Reaction Wheel (DMCR) in the current control mode. In current-mode, the required current is delivered to the coils in order to achieve the desired torque. During this research, all the friction parameters as viscous and coulomb, motor coefficient, resistance and voltage constant are identified. In order to model identification of a reaction wheel, numerous varying current commands apply on the particular wheel to verify the estimated model. All the parameters of DMCR are identified by classical Levenberg-Marquardt (CLM) optimization method. The experimental results demonstrate that the developed model has an appropriate precise and can be used in the satellite control simulation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=experimental%20modeling" title="experimental modeling">experimental modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=friction%20parameters" title=" friction parameters"> friction parameters</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20identification" title=" model identification"> model identification</a>, <a href="https://publications.waset.org/abstracts/search?q=reaction%20wheel" title=" reaction wheel"> reaction wheel</a> </p> <a href="https://publications.waset.org/abstracts/105328/an-optimal-approach-for-full-detailed-friction-model-identification-of-reaction-wheel" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/105328.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">233</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25047</span> Identification of Switched Reluctance Motor Parameters Using Exponential Swept-Sine Signal</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdelmalek%20Ouannou">Abdelmalek Ouannou</a>, <a href="https://publications.waset.org/abstracts/search?q=Adil%20Brouri"> Adil Brouri</a>, <a href="https://publications.waset.org/abstracts/search?q=Laila%20Kadi"> Laila Kadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Tarik"> Tarik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Switched reluctance motor (SRM) has a major interest in a large domain as in electric vehicle driving because of its wide range of speed operation, high performances, low cost, and robustness to run under degraded conditions. The purpose of the paper is to develop a new analytical approach for modeling SRM parameters. Then, an identification scheme is proposed to obtain the SRM parameters. Since the SRM is featured by a highly nonlinear behavior, modeling these devices is difficult. Then, it is convenient to develop an accurate model describing the SRM. Furthermore, it is always operated in the magnetically saturated mode to maximize the energy transfer. Accordingly, it is shown that the SRM can be accurately described by a generalized polynomial Hammerstein model, i.e., the parallel connection of several Hammerstein models having polynomial nonlinearity. Presently an analytical identification method is developed using a chirp excitation signal. Afterward, the parameters of the obtained model have been determined using Finite Element Method analysis. Finally, in order to show the effectiveness of the proposed method, a comparison between the true and estimate models has been performed. The obtained results show that the output responses are very close. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=switched%20reluctance%20motor" title="switched reluctance motor">switched reluctance motor</a>, <a href="https://publications.waset.org/abstracts/search?q=swept-sine%20signal" title=" swept-sine signal"> swept-sine signal</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20Hammerstein%20model" title=" generalized Hammerstein model"> generalized Hammerstein model</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20system" title=" nonlinear system"> nonlinear system</a> </p> <a href="https://publications.waset.org/abstracts/136961/identification-of-switched-reluctance-motor-parameters-using-exponential-swept-sine-signal" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/136961.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">237</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25046</span> Soil Parameters Identification around PMT Test by Inverse Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=I.%20Toumi">I. Toumi</a>, <a href="https://publications.waset.org/abstracts/search?q=Y.%20Abed"> Y. Abed</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Bouafia"> A. Bouafia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a methodology for identifying the cohesive soil parameters that takes into account different constitutive equations. The procedure, applied to identify the parameters of generalized Prager model associated to the Drucker & Prager failure criterion from a pressuremeter expansion curve, is based on an inverse analysis approach, which consists of minimizing the function representing the difference between the experimental curve and the simulated curve using a simplex algorithm. The model response on pressuremeter path and its identification from experimental data lead to the determination of the friction angle, the cohesion and the Young modulus. Some parameters effects on the simulated curves and stresses path around pressuremeter probe are presented. Comparisons between the parameters determined with the proposed method and those obtained by other means are also presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cohesive%20soils" title="cohesive soils">cohesive soils</a>, <a href="https://publications.waset.org/abstracts/search?q=cavity%20expansion" title=" cavity expansion"> cavity expansion</a>, <a href="https://publications.waset.org/abstracts/search?q=pressuremeter%20test" title=" pressuremeter test"> pressuremeter test</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20element%20method" title=" finite element method"> finite element method</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization%20procedure" title=" optimization procedure"> optimization procedure</a>, <a href="https://publications.waset.org/abstracts/search?q=simplex%20algorithm" title=" simplex algorithm"> simplex algorithm</a> </p> <a href="https://publications.waset.org/abstracts/49462/soil-parameters-identification-around-pmt-test-by-inverse-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49462.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">294</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25045</span> Identification of Nonlinear Systems Structured by Hammerstein-Wiener Model </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Brouri">A. Brouri</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Giri"> F. Giri</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Mkhida"> A. Mkhida</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Elkarkri"> A. Elkarkri</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20L.%20Chhibat"> M. L. Chhibat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Standard Hammerstein-Wiener models consist of a linear subsystem sandwiched by two memoryless nonlinearities. Presently, the linear subsystem is allowed to be parametric or not, continuous- or discrete-time. The input and output nonlinearities are polynomial and may be noninvertible. A two-stage identification method is developed such the parameters of all nonlinear elements are estimated first using the Kozen-Landau polynomial decomposition algorithm. The obtained estimates are then based upon in the identification of the linear subsystem, making use of suitable pre-ad post-compensators. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20system%20identification" title="nonlinear system identification">nonlinear system identification</a>, <a href="https://publications.waset.org/abstracts/search?q=Hammerstein-Wiener%20systems" title=" Hammerstein-Wiener systems"> Hammerstein-Wiener systems</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency%20identification" title=" frequency identification"> frequency identification</a>, <a href="https://publications.waset.org/abstracts/search?q=polynomial%20decomposition" title=" polynomial decomposition"> polynomial decomposition</a> </p> <a href="https://publications.waset.org/abstracts/7969/identification-of-nonlinear-systems-structured-by-hammerstein-wiener-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7969.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">511</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25044</span> The Gasoil Hydrofining Kinetics Constants Identification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=C.%20Patrascioiu">C. Patrascioiu</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20Matei"> V. Matei</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Nicolae"> N. Nicolae</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper describes the experiments and the kinetic parameters calculus of the gasoil hydrofining. They are presented experimental results of gasoil hidrofining using Mo and promoted with Ni on aluminum support catalyst. The authors have adapted a kinetic model gasoil hydrofining. Using this proposed kinetic model and the experimental data they have calculated the parameters of the model. The numerical calculus is based on minimizing the difference between the experimental sulf concentration and kinetic model estimation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hydrofining" title="hydrofining">hydrofining</a>, <a href="https://publications.waset.org/abstracts/search?q=kinetic" title=" kinetic"> kinetic</a>, <a href="https://publications.waset.org/abstracts/search?q=modeling" title=" modeling"> modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a> </p> <a href="https://publications.waset.org/abstracts/14522/the-gasoil-hydrofining-kinetics-constants-identification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14522.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">438</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25043</span> Nonlinear Aerodynamic Parameter Estimation of a Supersonic Air to Air Missile by Using Artificial Neural Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tugba%20Bayoglu">Tugba Bayoglu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=air%20to%20air%20missile" title="air to air missile">air to air missile</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title=" artificial neural networks"> artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=open%20loop%20simulation" title=" open loop simulation"> open loop simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20identification" title=" parameter identification"> parameter identification</a> </p> <a href="https://publications.waset.org/abstracts/72976/nonlinear-aerodynamic-parameter-estimation-of-a-supersonic-air-to-air-missile-by-using-artificial-neural-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72976.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">279</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25042</span> Identification and Control the Yaw Motion Dynamics of Open Frame Underwater Vehicle </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mirza%20Mohibulla%20Baig">Mirza Mohibulla Baig</a>, <a href="https://publications.waset.org/abstracts/search?q=Imil%20Hamda%20Imran"> Imil Hamda Imran</a>, <a href="https://publications.waset.org/abstracts/search?q=Tri%20Bagus%20Susilo"> Tri Bagus Susilo</a>, <a href="https://publications.waset.org/abstracts/search?q=Sami%20El%20Ferik"> Sami El Ferik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper deals with system identification and control a nonlinear model of semi-autonomous underwater vehicle (UUV). The input-output data is first generated using the experimental values of the model parameters and then this data is used to compute the estimated parameter values. In this study, we use the semi-autonomous UUV LAURS model, which is developed by the Sensors and Actuators Laboratory in University of Sao Paolo. We applied three methods to identify the parameters: integral method, which is a classical least square method, recursive least square, and weighted recursive least square. In this paper, we also apply three different inputs (step input, sine wave input and random input) to each identification method. After the identification stage, we investigate the control performance of yaw motion of nonlinear semi-autonomous Unmanned Underwater Vehicle (UUV) using feedback linearization-based controller. In addition, we compare the performance of the control with an integral and a non-integral part along with state feedback. Finally, disturbance rejection and resilience of the controller is tested. The results demonstrate the ability of the system to recover from such fault. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=system%20identification" title="system identification">system identification</a>, <a href="https://publications.waset.org/abstracts/search?q=underwater%20vehicle" title=" underwater vehicle"> underwater vehicle</a>, <a href="https://publications.waset.org/abstracts/search?q=integral%20method" title=" integral method"> integral method</a>, <a href="https://publications.waset.org/abstracts/search?q=recursive%20least%20square" title=" recursive least square"> recursive least square</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20recursive%20least%20square" title=" weighted recursive least square"> weighted recursive least square</a>, <a href="https://publications.waset.org/abstracts/search?q=feedback%20linearization" title=" feedback linearization"> feedback linearization</a>, <a href="https://publications.waset.org/abstracts/search?q=integral%20error" title=" integral error"> integral error</a> </p> <a href="https://publications.waset.org/abstracts/21830/identification-and-control-the-yaw-motion-dynamics-of-open-frame-underwater-vehicle" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21830.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">536</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25041</span> Identification of Impact Load and Partial System Parameters Using 1D-CNN</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xuewen%20Yu">Xuewen Yu</a>, <a href="https://publications.waset.org/abstracts/search?q=Danhui%20Dan"> Danhui Dan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The identification of impact load and some hard-to-obtain system parameters is crucial for the activities of analysis, validation, and evaluation in the engineering field. This paper proposes a method that utilizes neural networks based on 1D-CNN to identify the impact load and partial system parameters from measured responses. To this end, forward computations are conducted to provide datasets consisting of the triples (parameter θ, input u, output y). Then neural networks are trained to learn the mapping from input to output, fu|{θ} : y → u, as well as from input and output to parameter, fθ : (u, y) → θ. Afterward, feeding the trained neural networks the measured output response, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=convolutional%20neural%20network" title="convolutional neural network">convolutional neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=impact%20load%20identification" title=" impact load identification"> impact load identification</a>, <a href="https://publications.waset.org/abstracts/search?q=system%20parameter%20identification" title=" system parameter identification"> system parameter identification</a>, <a href="https://publications.waset.org/abstracts/search?q=inverse%20problem" title=" inverse problem"> inverse problem</a> </p> <a href="https://publications.waset.org/abstracts/173755/identification-of-impact-load-and-partial-system-parameters-using-1d-cnn" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/173755.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">123</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25040</span> Identification of Wiener Model Using Iterative Schemes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vikram%20Saini">Vikram Saini</a>, <a href="https://publications.waset.org/abstracts/search?q=Lillie%20Dewan"> Lillie Dewan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hard%20non-linearity" title="hard non-linearity">hard non-linearity</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20square" title=" least square"> least square</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20estimation" title=" parameter estimation"> parameter estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20approximation%20gradient" title=" stochastic approximation gradient"> stochastic approximation gradient</a>, <a href="https://publications.waset.org/abstracts/search?q=Wiener%20model" title=" Wiener model"> Wiener model</a> </p> <a href="https://publications.waset.org/abstracts/70632/identification-of-wiener-model-using-iterative-schemes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70632.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">405</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25039</span> Linear MIMO Model Identification Using an Extended Kalman Filter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Matthew%20C.%20Best">Matthew C. Best</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=system%20identification" title="system identification">system identification</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20model" title=" linear model"> linear model</a>, <a href="https://publications.waset.org/abstracts/search?q=MIMO" title=" MIMO"> MIMO</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20order%20reduction" title=" model order reduction"> model order reduction</a> </p> <a href="https://publications.waset.org/abstracts/24532/linear-mimo-model-identification-using-an-extended-kalman-filter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24532.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">594</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25038</span> Damage Identification in Reinforced Concrete Beams Using Modal Parameters and Their Formulation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Al-Ghalib">Ali Al-Ghalib</a>, <a href="https://publications.waset.org/abstracts/search?q=Fouad%20Mohammad"> Fouad Mohammad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The identification of damage in reinforced concrete structures subjected to incremental cracking performance exploiting vibration data is recognized as a challenging topic in the published and heavily cited literature. Therefore, this paper attempts to shine light on the extent of dynamic methods when applied to reinforced concrete beams simulated with various scenarios of defects. For this purpose, three different reinforced concrete beams are tested through the course of the study. The three beams are loaded statically to failure in incremental successive load cycles and later rehabilitated. After each static load stage, the beams are tested under free-free support condition using experimental modal analysis. The beams were all of the same length and cross-sectional area (2.0x0.14x0.09)m, but they were different in concrete compressive strength and the type of damage presented. The experimental modal parameters as damage identification parameters were showed computationally expensive, time consuming and require substantial inputs and considerable expertise. Nonetheless, they were proved plausible for the condition monitoring of the current case study as well as structural changes in the course of progressive loads. It was accentuated that a satisfactory localization and quantification for structural changes (Level 2 and Level 3 of damage identification problem) can only be achieved reasonably through considering frequencies and mode shapes of a system in a proper analytical model. A convenient post analysis process for various datasets of vibration measurements for the three beams is conducted in order to extract, check and correlate the basic modal parameters; namely, natural frequency, modal damping and mode shapes. The results of the extracted modal parameters and their combination are utilized and discussed in this research as quantification parameters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=experimental%20modal%20analysis" title="experimental modal analysis">experimental modal analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=damage%20identification" title=" damage identification"> damage identification</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20health%20monitoring" title=" structural health monitoring"> structural health monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=reinforced%20concrete%20beam" title=" reinforced concrete beam"> reinforced concrete beam</a> </p> <a href="https://publications.waset.org/abstracts/59519/damage-identification-in-reinforced-concrete-beams-using-modal-parameters-and-their-formulation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59519.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">263</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25037</span> A Data-Mining Model for Protection of FACTS-Based Transmission Line</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ashok%20Kalagura">Ashok Kalagura</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a data-mining model for fault-zone identification of ﬂexible AC transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-ﬂow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides an effective decision on the fault-zone identification. Half-cycle post-fault current and voltage samples from the fault inception are used as an input vector against target output ‘1’ for the fault after TCSC/UPFC and ‘1’ for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate the reliable identification of the fault zone in FACTS-based transmission lines. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distance%20relaying" title="distance relaying">distance relaying</a>, <a href="https://publications.waset.org/abstracts/search?q=fault-zone%20identification" title=" fault-zone identification"> fault-zone identification</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20forests" title=" random forests"> random forests</a>, <a href="https://publications.waset.org/abstracts/search?q=RFs" title=" RFs"> RFs</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM" title=" SVM"> SVM</a>, <a href="https://publications.waset.org/abstracts/search?q=thyristor-controlled%20series%20compensator" title=" thyristor-controlled series compensator"> thyristor-controlled series compensator</a>, <a href="https://publications.waset.org/abstracts/search?q=TCSC" title=" TCSC"> TCSC</a>, <a href="https://publications.waset.org/abstracts/search?q=unified%20power-%EF%AC%82ow%20controller" title=" unified power-ﬂow controller"> unified power-ﬂow controller</a>, <a href="https://publications.waset.org/abstracts/search?q=UPFC" title=" UPFC "> UPFC </a> </p> <a href="https://publications.waset.org/abstracts/32579/a-data-mining-model-for-protection-of-facts-based-transmission-line" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32579.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">423</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25036</span> Post-Earthquake Damage Detection Using System Identification with a Pair of Seismic Recordings</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lotfi%20O.%20Gargab">Lotfi O. Gargab</a>, <a href="https://publications.waset.org/abstracts/search?q=Ruichong%20R.%20Zhang"> Ruichong R. Zhang </a> </p> <p class="card-text"><strong>Abstract:</strong></p> A wave-based framework is presented for modeling seismic motion in multistory buildings and using measured response for system identification which can be utilized to extract important information regarding structure integrity. With one pair of building response at two locations, a generalized model response is formulated based on wave propagation features and expressed as frequency and time response functions denoted, respectively, as GFRF and GIRF. In particular, GIRF is fundamental in tracking arrival times of impulsive wave motion initiated at response level which is dependent on local model properties. Matching model and measured-structure responses can help in identifying model parameters and infer building properties. To show the effectiveness of this approach, the Millikan Library in Pasadena, California is identified with recordings of the Yorba Linda earthquake of September 3, 2002. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=system%20identification" title="system identification">system identification</a>, <a href="https://publications.waset.org/abstracts/search?q=continuous-discrete%20mass%20modeling" title=" continuous-discrete mass modeling"> continuous-discrete mass modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=damage%20detection" title=" damage detection"> damage detection</a>, <a href="https://publications.waset.org/abstracts/search?q=post-earthquake" title=" post-earthquake"> post-earthquake</a> </p> <a href="https://publications.waset.org/abstracts/7612/post-earthquake-damage-detection-using-system-identification-with-a-pair-of-seismic-recordings" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7612.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">369</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25035</span> Control Algorithm for Home Automation Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marek%20D%C5%82ugosz">Marek Długosz</a>, <a href="https://publications.waset.org/abstracts/search?q=Pawe%C5%82%20Skruch"> Paweł Skruch</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of purposes of home automation systems is to provide appropriate comfort to the users by suitable air temperature control and stabilization inside the rooms. The control of temperature level is not a simple task and the basic difficulty results from the fact that accurate parameters of the object of control, that is a building, remain unknown. Whereas the structure of the model is known, the identification of model parameters is a difficult task. In this paper, a control algorithm allowing the present temperature to be reached inside the building within the specified time without the need to know accurate parameters of the building itself is presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=control" title="control">control</a>, <a href="https://publications.waset.org/abstracts/search?q=home%20automation%20system" title=" home automation system"> home automation system</a>, <a href="https://publications.waset.org/abstracts/search?q=wireless%20networking" title=" wireless networking"> wireless networking</a>, <a href="https://publications.waset.org/abstracts/search?q=automation%20engineering" title=" automation engineering"> automation engineering</a> </p> <a href="https://publications.waset.org/abstracts/6970/control-algorithm-for-home-automation-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6970.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">618</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25034</span> Parameters Identification of Granular Soils around PMT Test by Inverse Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Younes%20Abed">Younes Abed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The successful application of in-situ testing of soils heavily depends on development of interpretation methods of tests. The pressuremeter test simulates the expansion of a cylindrical cavity and because it has well defined boundary conditions, it is more unable to rigorous theoretical analysis (i. e. cavity expansion theory) then most other in-situ tests. In this article, and in order to make the identification process more convenient, we propose a relatively simple procedure which involves the numerical identification of some mechanical parameters of a granular soil, especially, the elastic modulus and the friction angle from a pressuremeter curve. The procedure, applied here to identify the parameters of generalised prager model associated to the Drucker & Prager criterion from a pressuremeter curve, is based on an inverse analysis approach, which consists of minimizing the function representing the difference between the experimental curve and the curve obtained by integrating the model along the loading path in in-situ testing. The numerical process implemented here is based on the established finite element program. We present a validation of the proposed approach by a database of tests on expansion of cylindrical cavity. This database consists of four types of tests; thick cylinder tests carried out on the Hostun RF sand, pressuremeter tests carried out on the Hostun sand, in-situ pressuremeter tests carried out at the site of Fos with marine self-boring pressuremeter and in-situ pressuremeter tests realized on the site of Labenne with Menard pressuremeter. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=granular%20soils" title="granular soils">granular soils</a>, <a href="https://publications.waset.org/abstracts/search?q=cavity%20expansion" title=" cavity expansion"> cavity expansion</a>, <a href="https://publications.waset.org/abstracts/search?q=pressuremeter%20test" title=" pressuremeter test"> pressuremeter test</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20element%20method" title=" finite element method"> finite element method</a>, <a href="https://publications.waset.org/abstracts/search?q=identification%20procedure" title=" identification procedure"> identification procedure</a> </p> <a href="https://publications.waset.org/abstracts/2474/parameters-identification-of-granular-soils-around-pmt-test-by-inverse-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2474.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">292</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25033</span> Reliable Line-of-Sight and Non-Line-of-Sight Propagation Channel Identification in Ultra-Wideband Wireless Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Adnan%20Landolsi">Mohamed Adnan Landolsi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ali%20F.%20Almutairi"> Ali F. Almutairi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper addresses the problem of line-of-sight (LOS) vs. non-line-of-sight (NLOS) propagation link identification in ultra-wideband (UWB) wireless networks, which is necessary for improving the accuracy of radiolocation and positioning applications. A LOS/NLOS likelihood hypothesis testing approach is applied based on exploiting distinctive statistical features of the channel impulse response (CIR) using parameters related to the “skewness” of the CIR and its root mean square (RMS) delay spread. A log-normal fit is presented for the probability densities of the CIR parameters. Simulation results show that different environments (residential, office, outdoor, etc.) have measurable differences in their CIR parameters’ statistics, which is then exploited in determining the nature of the propagation channels. Correct LOS/NLOS channel identification rates exceeding 90% are shown to be achievable for most types of environments. Additional improvement is also obtained by combining both CIR skewness and RMS delay statistics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=UWB" title="UWB">UWB</a>, <a href="https://publications.waset.org/abstracts/search?q=propagation" title=" propagation"> propagation</a>, <a href="https://publications.waset.org/abstracts/search?q=LOS" title=" LOS"> LOS</a>, <a href="https://publications.waset.org/abstracts/search?q=NLOS" title=" NLOS"> NLOS</a>, <a href="https://publications.waset.org/abstracts/search?q=identification" title=" identification"> identification</a> </p> <a href="https://publications.waset.org/abstracts/55684/reliable-line-of-sight-and-non-line-of-sight-propagation-channel-identification-in-ultra-wideband-wireless-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55684.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">249</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25032</span> Kalman Filter Design in Structural Identification with Unknown Excitation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Z.%20Masoumi">Z. Masoumi</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Moaveni"> B. Moaveni</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This article is about first step of structural health monitoring by identifying structural system in the presence of unknown input. In the structural system identification, identification of structural parameters such as stiffness and damping are considered. In this study, the Kalman filter (KF) design for structural systems with unknown excitation is expressed. External excitations, such as earthquakes, wind or any other forces are not measured or not available. The purpose of this filter is its strengths to estimate the state variables of the system in the presence of unknown input. Also least squares estimation (LSE) method with unknown input is studied. Estimates of parameters have been adopted. Finally, using two examples advantages and drawbacks of both methods are studied. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter%20%28KF%29" title="Kalman filter (KF)">Kalman filter (KF)</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20square%20estimation%20%28LSE%29" title=" least square estimation (LSE)"> least square estimation (LSE)</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20health%20monitoring%20%28SHM%29" title=" structural health monitoring (SHM)"> structural health monitoring (SHM)</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20system%20identification" title=" structural system identification"> structural system identification</a> </p> <a href="https://publications.waset.org/abstracts/49817/kalman-filter-design-in-structural-identification-with-unknown-excitation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49817.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">317</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25031</span> Identification of Vehicle Dynamic Parameters by Using Optimized Exciting Trajectory on 3- DOF Parallel Manipulator</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Di%20Yao">Di Yao</a>, <a href="https://publications.waset.org/abstracts/search?q=Gunther%20Prokop"> Gunther Prokop</a>, <a href="https://publications.waset.org/abstracts/search?q=Kay%20Buttner"> Kay Buttner</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Dynamic parameters, including the center of gravity, mass and inertia moments of vehicle, play an essential role in vehicle simulation, collision test and real-time control of vehicle active systems. To identify the important vehicle dynamic parameters, a systematic parameter identification procedure is studied in this work. In the first step of the procedure, a conceptual parallel manipulator (virtual test rig), which possesses three rotational degrees-of-freedom, is firstly proposed. To realize kinematic characteristics of the conceptual parallel manipulator, the kinematic analysis consists of inverse kinematic and singularity architecture is carried out. Based on the Euler's rotation equations for rigid body dynamics, the dynamic model of parallel manipulator and derivation of measurement matrix for parameter identification are presented subsequently. In order to reduce the sensitivity of parameter identification to measurement noise and other unexpected disturbances, a parameter optimization process of searching for optimal exciting trajectory of parallel manipulator is conducted in the following section. For this purpose, the 321-Euler-angles defined by parameterized finite-Fourier-series are primarily used to describe the general exciting trajectory of parallel manipulator. To minimize the condition number of measurement matrix for achieving better parameter identification accuracy, the unknown coefficients of parameterized finite-Fourier-series are estimated by employing an iterative algorithm based on MATLAB®. Meanwhile, the iterative algorithm will ensure the parallel manipulator still keeps in an achievable working status during the execution of optimal exciting trajectory. It is showed that the proposed procedure and methods in this work can effectively identify the vehicle dynamic parameters and could be an important application of parallel manipulator in the fields of parameter identification and test rig development. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=parameter%20identification" title="parameter identification">parameter identification</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20manipulator" title=" parallel manipulator"> parallel manipulator</a>, <a href="https://publications.waset.org/abstracts/search?q=singularity%20architecture" title=" singularity architecture"> singularity architecture</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20modelling" title=" dynamic modelling"> dynamic modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=exciting%20trajectory" title=" exciting trajectory"> exciting trajectory</a> </p> <a href="https://publications.waset.org/abstracts/89199/identification-of-vehicle-dynamic-parameters-by-using-optimized-exciting-trajectory-on-3-dof-parallel-manipulator" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/89199.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">266</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25030</span> Parameter Identification Analysis in the Design of Rock Fill Dams</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20Shahzadi">G. Shahzadi</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Soulaimani"> A. Soulaimani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rockfill%20dam" title="Rockfill dam">Rockfill dam</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20identification" title=" parameter identification"> parameter identification</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20analysis" title=" stochastic analysis"> stochastic analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=regression" title=" regression"> regression</a>, <a href="https://publications.waset.org/abstracts/search?q=PLAXIS" title=" PLAXIS"> PLAXIS</a> </p> <a href="https://publications.waset.org/abstracts/110580/parameter-identification-analysis-in-the-design-of-rock-fill-dams" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110580.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">146</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25029</span> Mathematical Modeling of Activated Sludge Process: Identification and Optimization of Key Design Parameters </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ujwal%20Kishor%20Zore">Ujwal Kishor Zore</a>, <a href="https://publications.waset.org/abstracts/search?q=Shankar%20Balajirao%20Kausley"> Shankar Balajirao Kausley</a>, <a href="https://publications.waset.org/abstracts/search?q=Aniruddha%20Bhalchandra%20Pandit"> Aniruddha Bhalchandra Pandit</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There are some important design parameters of activated sludge process (ASP) for wastewater treatment and they must be optimally defined to have the optimized plant working. To know them, developing a mathematical model is a way out as it is nearly commensurate the real world works. In this study, a mathematical model was developed for ASP, solved under activated sludge model no 1 (ASM 1) conditions and MATLAB tool was used to solve the mathematical equations. For its real-life validation, the developed model was tested for the inputs from the municipal wastewater treatment plant and the results were quite promising. Additionally, the most cardinal assumptions required to design the treatment plant are discussed in this paper. With the need for computerization and digitalization surging in every aspect of engineering, this mathematical model developed might prove to be a boon to many biological wastewater treatment plants as now they can in no time know the design parameters which are required for a particular type of wastewater treatment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=waste%20water%20treatment" title="waste water treatment">waste water treatment</a>, <a href="https://publications.waset.org/abstracts/search?q=activated%20sludge%20process" title=" activated sludge process"> activated sludge process</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20modeling" title=" mathematical modeling"> mathematical modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a> </p> <a href="https://publications.waset.org/abstracts/112745/mathematical-modeling-of-activated-sludge-process-identification-and-optimization-of-key-design-parameters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/112745.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">144</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25028</span> A Study on Reliability of Gender and Stature Determination by Odontometric and Craniofacial Anthropometric Parameters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Churamani%20Pokhrel">Churamani Pokhrel</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20B.%20Jha"> C. B. Jha</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20R.%20Niraula"> S. R. Niraula</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20R.%20Pokharel"> P. R. Pokharel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Human identification is one of the most challenging subjects that man has confronted. The determination of adult sex and stature are two of the four key factors (sex, stature, age, and race) in identification of an individual. Craniofacial and odontometric parameters are important tools for forensic anthropologists when it is not possible to apply advanced techniques for identification purposes. The present study provides anthropometric correlation of the parameters with stature and gender and also devises regression formulae for reconstruction of stature. A total of 312 Nepalese students with equal distribution of sex i.e., 156 male and 156 female students of age 18-35 years were taken for the study. Total of 10 parameters were measured (age, sex, stature, head circumference, head length, head breadth, facial height, bi-zygomatic width, mesio-distal canine width and inter-canine distance of both maxilla and mandible). Co-relation and regression analysis was done to find the association between the parameters. All parameters were found to be greater in males than females and each was found to be statistically significant. Out of total 312 samples, the best regressor for the determination of stature was head circumference and mandibular inter-canine width and that for gender was head circumference and right mandibular teeth. The accuracy of prediction was 83%. Regression equations and analysis generated from craniofacial and odontometric parameters can be a supplementary approach for the estimation of stature and gender when extremities are not available. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=craniofacial" title="craniofacial">craniofacial</a>, <a href="https://publications.waset.org/abstracts/search?q=gender" title=" gender"> gender</a>, <a href="https://publications.waset.org/abstracts/search?q=odontometric" title=" odontometric"> odontometric</a>, <a href="https://publications.waset.org/abstracts/search?q=stature" title=" stature"> stature</a> </p> <a href="https://publications.waset.org/abstracts/83118/a-study-on-reliability-of-gender-and-stature-determination-by-odontometric-and-craniofacial-anthropometric-parameters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/83118.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">191</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=6">6</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=7">7</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=8">8</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=9">9</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=10">10</a></li> <li class="page-item disabled"><span class="page-link">...</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=835">835</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=836">836</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=model%20parameters%20identification&page=2" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>