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control</title> <meta name="description" content="Search results for: type 2 fuzzy control"> <meta name="keywords" content="type 2 fuzzy control"> <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 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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="type 2 fuzzy control"> <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> 17073</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: type 2 fuzzy control</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17073</span> Interval Type-2 Fuzzy Vibration Control of an ERF Embedded Smart Structure</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chih-Jer%20Lin">Chih-Jer Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Chun-Ying%20Lee"> Chun-Ying Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Ying%20Liu"> Ying Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Chiang-Ho%20Cheng"> Chiang-Ho Cheng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electro-rheological%20fluid" title="electro-rheological fluid">electro-rheological fluid</a>, <a href="https://publications.waset.org/abstracts/search?q=semi-active%20vibration%20control" title=" semi-active vibration control"> semi-active vibration control</a>, <a href="https://publications.waset.org/abstracts/search?q=shock%20absorber" title=" shock absorber"> shock absorber</a>, <a href="https://publications.waset.org/abstracts/search?q=type%202%20fuzzy%20control" title=" type 2 fuzzy control "> type 2 fuzzy control </a> </p> <a href="https://publications.waset.org/abstracts/7630/interval-type-2-fuzzy-vibration-control-of-an-erf-embedded-smart-structure" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7630.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">447</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">17072</span> Improving Load Frequency Control of Multi-Area Power System by Considering Uncertainty by Using Optimized Type 2 Fuzzy Pid Controller with the Harmony Search Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mehrdad%20Mahmudizad">Mehrdad Mahmudizad</a>, <a href="https://publications.waset.org/abstracts/search?q=Roya%20Ahmadi%20Ahangar"> Roya Ahmadi Ahangar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the method of designing the type 2 fuzzy PID controllers in order to solve the problem of Load Frequency Control (LFC). The Harmony Search (HS) algorithm is used to regulate the measurement factors and the effect of uncertainty of membership functions of Interval Type 2 Fuzzy Proportional Integral Differential (IT2FPID) controllers in order to reduce the frequency deviation resulted from the load oscillations. The simulation results implicitly show that the performance of the proposed IT2FPID LFC in terms of error, settling time and resistance against different load oscillations is more appropriate and preferred than PID and Type 1 Fuzzy Proportional Integral Differential (T1FPID) controllers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=load%20frequency%20control" title="load frequency control">load frequency control</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy-pid%20controller" title=" fuzzy-pid controller"> fuzzy-pid controller</a>, <a href="https://publications.waset.org/abstracts/search?q=type%202%20fuzzy%20system" title=" type 2 fuzzy system"> type 2 fuzzy system</a>, <a href="https://publications.waset.org/abstracts/search?q=harmony%20search%20algorithm" title=" harmony search algorithm"> harmony search algorithm</a> </p> <a href="https://publications.waset.org/abstracts/52340/improving-load-frequency-control-of-multi-area-power-system-by-considering-uncertainty-by-using-optimized-type-2-fuzzy-pid-controller-with-the-harmony-search-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52340.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">278</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">17071</span> Performences of Type-2 Fuzzy Logic Control and Neuro-Fuzzy Control Based on DPC for Grid Connected DFIG with Fixed Switching Frequency</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fayssal%20Amrane">Fayssal Amrane</a>, <a href="https://publications.waset.org/abstracts/search?q=Azeddine%20Chaiba"> Azeddine Chaiba</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, type-2 fuzzy logic control (T2FLC) and neuro-fuzzy control (NFC) for a doubly fed induction generator (DFIG) based on direct power control (DPC) with a fixed switching frequency is proposed for wind generation application. First, a mathematical model of the doubly-fed induction generator implemented in d-q reference frame is achieved. Then, a DPC algorithm approach for controlling active and reactive power of DFIG via fixed switching frequency is incorporated using PID. The performance of T2FLC and NFC, which is based on the DPC algorithm, are investigated and compared to those obtained from the PID controller. Finally, simulation results demonstrate that the NFC is more robust, superior dynamic performance for wind power generation system applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=doubly%20fed%20induction%20generator%20%28DFIG%29" title="doubly fed induction generator (DFIG)">doubly fed induction generator (DFIG)</a>, <a href="https://publications.waset.org/abstracts/search?q=direct%20power%20control%20%28DPC%29" title=" direct power control (DPC)"> direct power control (DPC)</a>, <a href="https://publications.waset.org/abstracts/search?q=neuro-fuzzy%20control%20%28NFC%29" title=" neuro-fuzzy control (NFC)"> neuro-fuzzy control (NFC)</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20power%20point%20tracking%20%28MPPT%29" title=" maximum power point tracking (MPPT)"> maximum power point tracking (MPPT)</a>, <a href="https://publications.waset.org/abstracts/search?q=space%20vector%20modulation%20%28SVM%29" title=" space vector modulation (SVM)"> space vector modulation (SVM)</a>, <a href="https://publications.waset.org/abstracts/search?q=type%202%20fuzzy%20logic%20control%20%28T2FLC%29" title=" type 2 fuzzy logic control (T2FLC)"> type 2 fuzzy logic control (T2FLC)</a> </p> <a href="https://publications.waset.org/abstracts/48773/performences-of-type-2-fuzzy-logic-control-and-neuro-fuzzy-control-based-on-dpc-for-grid-connected-dfig-with-fixed-switching-frequency" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48773.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">419</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">17070</span> A Fuzzy Nonlinear Regression Model for Interval Type-2 Fuzzy Sets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=O.%20Poleshchuk">O. Poleshchuk</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Komarov"> E. Komarov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=interval%20type-2%20fuzzy%20sets" title="interval type-2 fuzzy sets">interval type-2 fuzzy sets</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20regression" title=" fuzzy regression"> fuzzy regression</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20interval" title=" weighted interval"> weighted interval</a> </p> <a href="https://publications.waset.org/abstracts/6138/a-fuzzy-nonlinear-regression-model-for-interval-type-2-fuzzy-sets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6138.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">373</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">17069</span> Fuzzy Control and Pertinence Functions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Luiz%20F.%20J.%20Maia">Luiz F. J. Maia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an approach to fuzzy control, with the use of new pertinence functions, applied in the case of an inverted pendulum. Appropriate definitions of pertinence functions to fuzzy sets make possible the implementation of the controller with only one control rule, resulting in a smooth control surface. The fuzzy control system can be implemented with analog devices, affording a true real-time performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=control%20surface" title="control surface">control surface</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20control" title=" fuzzy control"> fuzzy control</a>, <a href="https://publications.waset.org/abstracts/search?q=Inverted%20pendulum" title=" Inverted pendulum"> Inverted pendulum</a>, <a href="https://publications.waset.org/abstracts/search?q=pertinence%20functions" title=" pertinence functions"> pertinence functions</a> </p> <a href="https://publications.waset.org/abstracts/2467/fuzzy-control-and-pertinence-functions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2467.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">449</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">17068</span> From Type-I to Type-II Fuzzy System Modeling for Diagnosis of Hepatitis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shahabeddin%20Sotudian">Shahabeddin Sotudian</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20H.%20Fazel%20Zarandi"> M. H. Fazel Zarandi</a>, <a href="https://publications.waset.org/abstracts/search?q=I.%20B.%20Turksen"> I. B. Turksen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hepatitis%20disease" title="hepatitis disease">hepatitis disease</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20diagnosis" title=" medical diagnosis"> medical diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=type-I%20fuzzy%20logic" title=" type-I fuzzy logic"> type-I fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=type-II%20fuzzy%20logic" title=" type-II fuzzy logic"> type-II fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20selection" title=" feature selection"> feature selection</a> </p> <a href="https://publications.waset.org/abstracts/49654/from-type-i-to-type-ii-fuzzy-system-modeling-for-diagnosis-of-hepatitis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49654.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">306</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">17067</span> Caputo-Type Fuzzy Fractional Riccati Differential Equations with Fuzzy Initial Conditions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Trilok%20Mathur">Trilok Mathur</a>, <a href="https://publications.waset.org/abstracts/search?q=Shivi%20Agarwal"> Shivi Agarwal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper deals with the solutions of fuzzy-fractional-order Riccati equations under Caputo-type fuzzy fractional derivatives. The Caputo-type fuzzy fractional derivatives are defined based on Hukuhura difference and strongly generalized fuzzy differentiability. The Laplace-Adomian-Pade method is used for solving fractional Riccati-type initial value differential equations of fractional order. Moreover, we also displayed some examples to illustrate our methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Caputo-type%20fuzzy%20fractional%20derivative" title="Caputo-type fuzzy fractional derivative">Caputo-type fuzzy fractional derivative</a>, <a href="https://publications.waset.org/abstracts/search?q=Fractional%20Riccati%20differential%20equations" title=" Fractional Riccati differential equations"> Fractional Riccati differential equations</a>, <a href="https://publications.waset.org/abstracts/search?q=Laplace-Adomian-Pade%20method" title=" Laplace-Adomian-Pade method"> Laplace-Adomian-Pade method</a>, <a href="https://publications.waset.org/abstracts/search?q=Mittag%20Leffler%20function" title=" Mittag Leffler function"> Mittag Leffler function</a> </p> <a href="https://publications.waset.org/abstracts/51080/caputo-type-fuzzy-fractional-riccati-differential-equations-with-fuzzy-initial-conditions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51080.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">395</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">17066</span> Using Interval Type-2 Fuzzy Controller for Diabetes Mellitus </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nafiseh%20Mollaei">Nafiseh Mollaei</a>, <a href="https://publications.waset.org/abstracts/search?q=Reihaneh%20Kardehi%20Moghaddam"> Reihaneh Kardehi Moghaddam </a> </p> <p class="card-text"><strong>Abstract:</strong></p> In case of Diabetes Mellitus the controlling of insulin is very difficult. This illness is an incurable disease affecting millions of people worldwide. Glucose is a sugar which provides energy to the cells. Insulin is a hormone which supports the absorption of glucose. Fuzzy control strategy is attractive for glucose control because it mimics the first and second phase responses that the pancreas beta cells use to control glucose. We propose two control algorithms a type-1 fuzzy controller and an interval type-2 fuzzy method for the insulin infusion. The closed loop system has been simulated for different patients with different parameters, in present of the food intake disturbance and it has been shown that the blood glucose concentrations at a normoglycemic level of 110 mg/dl in the reasonable amount of time. This paper deals with type 1 diabetes as a nonlinear model, which has been simulated in MATLAB-SIMULINK environment. The novel model, termed the Augmented Minimal Model is used in the simulations. There are some uncertainties in this model due to factors such as blood glucose, daily meals or sudden stress. In addition to eliminate the effects of uncertainty, different control methods may be utilized. In this article, fuzzy controller performance were assessed in terms of its ability to track a normoglycemic set point (110 mg/dl) in response to a [0-10] g meal disturbance. Finally, the development reported in this paper is supposed to simplify the insulin delivery, so increasing the quality of life of the patient. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=interval%20type-2" title="interval type-2">interval type-2</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20controller" title=" fuzzy controller"> fuzzy controller</a>, <a href="https://publications.waset.org/abstracts/search?q=minimal%20augmented%20model" title=" minimal augmented model"> minimal augmented model</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertainty" title=" uncertainty"> uncertainty</a> </p> <a href="https://publications.waset.org/abstracts/16955/using-interval-type-2-fuzzy-controller-for-diabetes-mellitus" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16955.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">428</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">17065</span> Ant Lion Optimization in a Fuzzy System for Benchmark Control Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Leticia%20Cervantes">Leticia Cervantes</a>, <a href="https://publications.waset.org/abstracts/search?q=Edith%20Garcia"> Edith Garcia</a>, <a href="https://publications.waset.org/abstracts/search?q=Oscar%20Castillo"> Oscar Castillo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> At today, there are several control problems where the main objective is to obtain the best control in the study to decrease the error in the application. Many techniques can use to control these problems such as Neural Networks, PID control, Fuzzy Logic, Optimization techniques and many more. In this case, fuzzy logic with fuzzy system and an optimization technique are used to control the case of study. In this case, Ant Lion Optimization is used to optimize a fuzzy system to control the velocity of a simple treadmill. The main objective is to achieve the control of the velocity in the control problem using the ALO optimization. First, a simple fuzzy system was used to control the velocity of the treadmill it has two inputs (error and error change) and one output (desired speed), then results were obtained but to decrease the error the ALO optimization was developed to optimize the fuzzy system of the treadmill. Having the optimization, the simulation was performed, and results can prove that using the ALO optimization the control of the velocity was better than a conventional fuzzy system. This paper describes some basic concepts to help to understand the idea in this work, the methodology of the investigation (control problem, fuzzy system design, optimization), the results are presented and the optimization is used for the fuzzy system. A comparison between the simple fuzzy system and the optimized fuzzy systems are presented where it can be proving the optimization improved the control with good results the major findings of the study is that ALO optimization is a good alternative to improve the control because it helped to decrease the error in control applications even using any control technique to optimized, As a final statement is important to mentioned that the selected methodology was good because the control of the treadmill was improve using the optimization technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ant%20lion%20optimization" title="ant lion optimization">ant lion optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=control%20problem" title=" control problem"> control problem</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20control" title=" fuzzy control"> fuzzy control</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20system" title=" fuzzy system"> fuzzy system</a> </p> <a href="https://publications.waset.org/abstracts/88510/ant-lion-optimization-in-a-fuzzy-system-for-benchmark-control-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88510.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">399</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">17064</span> Fuzzy Logic Based Sliding Mode Controller for a New Soft Switching Boost Converter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Azam%20Salimi">Azam Salimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Majid%20Delshad"> Majid Delshad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a modified design of a sliding mode controller based on fuzzy logic for a New ZVThigh step up DC-DC Converter . Here a proportional - integral (PI)-type current mode control is employed and a sliding mode controller is designed utilizing fuzzy algorithm. Sliding mode controller guarantees robustness against all variations and fuzzy logic helps to reduce chattering phenomenon due to sliding controller, in that way efficiency increases and error, voltage and current ripples decreases. The proposed system is simulated using MATLAB / SIMULINK. This model is tested under variations of input and reference voltages and it was found that in comparison with conventional sliding mode controllers they perform better. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=switching%20mode%20power%20supplies" title="switching mode power supplies">switching mode power supplies</a>, <a href="https://publications.waset.org/abstracts/search?q=DC-DC%20converters" title=" DC-DC converters"> DC-DC converters</a>, <a href="https://publications.waset.org/abstracts/search?q=sliding%20mode%20control" title=" sliding mode control"> sliding mode control</a>, <a href="https://publications.waset.org/abstracts/search?q=robustness" title=" robustness"> robustness</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20control" title=" fuzzy control"> fuzzy control</a>, <a href="https://publications.waset.org/abstracts/search?q=current%20mode%20control" title=" current mode control"> current mode control</a>, <a href="https://publications.waset.org/abstracts/search?q=non-linear%20behavior" title=" non-linear behavior"> non-linear behavior</a> </p> <a href="https://publications.waset.org/abstracts/28763/fuzzy-logic-based-sliding-mode-controller-for-a-new-soft-switching-boost-converter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28763.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">539</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">17063</span> Fuzzy Logic Control for Flexible Joint Manipulator: An Experimental Implementation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sophia%20Fry">Sophia Fry</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahir%20Irtiza"> Mahir Irtiza</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexa%20Hoffman"> Alexa Hoffman</a>, <a href="https://publications.waset.org/abstracts/search?q=Yousef%20Sardahi"> Yousef Sardahi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study presents an intelligent control algorithm for a flexible robotic arm. Fuzzy control is used to control the motion of the arm to maintain the arm tip at the desired position while reducing vibration and increasing the system speed of response. The Fuzzy controller (FC) is based on adding the tip angular position to the arm deflection angle and using their sum as a feedback signal to the control algorithm. This reduces the complexity of the FC in terms of the input variables, number of membership functions, fuzzy rules, and control structure. Also, the design of the fuzzy controller is model-free and uses only our knowledge about the system. To show the efficacy of the FC, the control algorithm is implemented on the flexible joint manipulator (FJM) developed by Quanser. The results show that the proposed control method is effective in terms of response time, overshoot, and vibration amplitude. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic%20control" title="fuzzy logic control">fuzzy logic control</a>, <a href="https://publications.waset.org/abstracts/search?q=model-free%20control" title=" model-free control"> model-free control</a>, <a href="https://publications.waset.org/abstracts/search?q=flexible%20joint%20manipulators" title=" flexible joint manipulators"> flexible joint manipulators</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20control" title=" nonlinear control"> nonlinear control</a> </p> <a href="https://publications.waset.org/abstracts/164512/fuzzy-logic-control-for-flexible-joint-manipulator-an-experimental-implementation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164512.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">118</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">17062</span> Robustness of the Fuzzy Adaptive Speed Control of a Multi-Phase Asynchronous Machine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bessaad%20Taieb">Bessaad Taieb</a>, <a href="https://publications.waset.org/abstracts/search?q=Benbouali%20Abderrahmen"> Benbouali Abderrahmen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fuzzy controllers are a powerful tool for controlling complex processes. However, its robustness capacity remains moderately limited because it loses its property for large ranges of parametric variations. In this paper, the proposed control method is designed, based on a fuzzy adaptive controller used as a remedy for this problem. For increase the robustness of the vector control and to maintain the performance of the five-phase asynchronous machine despite the presence of disturbances (variation of rotor resistance, rotor inertia variations, sudden variations in the load etc.), by applying the method of behaviour model control (BMC). The results of simulation show that the fuzzy adaptive control provides best performance and has a more robustness as the fuzzy (FLC) and as a conventional (PI) controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20adaptive%20control" title="fuzzy adaptive control">fuzzy adaptive control</a>, <a href="https://publications.waset.org/abstracts/search?q=behaviour%20model%20control" title=" behaviour model control"> behaviour model control</a>, <a href="https://publications.waset.org/abstracts/search?q=vector%20control" title=" vector control"> vector control</a>, <a href="https://publications.waset.org/abstracts/search?q=five-phase%20asynchronous%20machine" title=" five-phase asynchronous machine"> five-phase asynchronous machine</a> </p> <a href="https://publications.waset.org/abstracts/168082/robustness-of-the-fuzzy-adaptive-speed-control-of-a-multi-phase-asynchronous-machine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168082.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">95</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">17061</span> Control of Single Axis Magnetic Levitation System Using Fuzzy Logic Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20M.%20Benomair">A. M. Benomair</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20O.%20Tokhi"> M. O. Tokhi </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the investigation on a system model for the stabilization of a Magnetic Levitation System (Maglev’s). The magnetic levitation system is a challenging nonlinear mechatronic system in which an electromagnetic force is required to suspend an object (metal sphere) in air space. The electromagnetic force is very sensitive to the noise which can create acceleration forces on the metal sphere, causing the sphere to move into the unbalanced region. Maglev’s give the contribution in industry and this system has reduce the power consumption, has increase the power efficiency and reduce the cost maintenance. The common applications for Maglev’s Power Generation (e.g. wind turbine), Maglev’s trains and Medical Device (e.g. Magnetically suspended Artificial Heart Pump). This paper presents the comparison between dynamic response and robust characteristic for both conventional PD and Fuzzy PD controller. The main contribution of this paper is the proof of fuzzy PD type stabilization and robustness. By use of a method to tune the scaling factors of the linear PD type fuzzy controller from an equivalent tuned conventional PD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=magnetic%20levitation%20system" title="magnetic levitation system">magnetic levitation system</a>, <a href="https://publications.waset.org/abstracts/search?q=PD%20controller" title=" PD controller"> PD controller</a>, <a href="https://publications.waset.org/abstracts/search?q=Fuzzy%20Logic%20Control" title=" Fuzzy Logic Control"> Fuzzy Logic Control</a>, <a href="https://publications.waset.org/abstracts/search?q=Fuzzy%20PD" title=" Fuzzy PD"> Fuzzy PD</a> </p> <a href="https://publications.waset.org/abstracts/19255/control-of-single-axis-magnetic-levitation-system-using-fuzzy-logic-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19255.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">273</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">17060</span> Sensitivity Analysis in Fuzzy Linear Programming Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20H.%20Nasseri">S. H. Nasseri</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Ebrahimnejad"> A. Ebrahimnejad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fuzzy set theory has been applied to many fields, such as operations research, control theory, and management sciences. In this paper, we consider two classes of fuzzy linear programming (FLP) problems: Fuzzy number linear programming and linear programming with trapezoidal fuzzy variables problems. We state our recently established results and develop fuzzy primal simplex algorithms for solving these problems. Finally, we give illustrative examples. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20linear%20programming" title="fuzzy linear programming">fuzzy linear programming</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20numbers" title=" fuzzy numbers"> fuzzy numbers</a>, <a href="https://publications.waset.org/abstracts/search?q=duality" title=" duality"> duality</a>, <a href="https://publications.waset.org/abstracts/search?q=sensitivity%20analysis" title=" sensitivity analysis"> sensitivity analysis</a> </p> <a href="https://publications.waset.org/abstracts/16916/sensitivity-analysis-in-fuzzy-linear-programming-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16916.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">565</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">17059</span> Fuzzy-Sliding Controller Design for Induction Motor Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Bouferhane">M. Bouferhane</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Boukhebza"> A. Boukhebza</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Hatab"> L. Hatab</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the position control of linear induction motor using fuzzy sliding mode controller design is proposed. First, the indirect field oriented control LIM is derived. Then, a designed sliding mode control system with an integral-operation switching surface is investigated, in which a simple adaptive algorithm is utilized for generalised soft-switching parameter. Finally, a fuzzy sliding mode controller is derived to compensate the uncertainties which occur in the control, in which the fuzzy logic system is used to dynamically control parameter settings of the SMC control law. The effectiveness of the proposed control scheme is verified by numerical simulation. The experimental results of the proposed scheme have presented good performances compared to the conventional sliding mode controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=linear%20induction%20motor" title="linear induction motor">linear induction motor</a>, <a href="https://publications.waset.org/abstracts/search?q=vector%20control" title=" vector control"> vector control</a>, <a href="https://publications.waset.org/abstracts/search?q=backstepping" title=" backstepping"> backstepping</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy-sliding%20mode%20control" title=" fuzzy-sliding mode control"> fuzzy-sliding mode control</a> </p> <a href="https://publications.waset.org/abstracts/44272/fuzzy-sliding-controller-design-for-induction-motor-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44272.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">489</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">17058</span> Lateral Control of Electric Vehicle Based on Fuzzy Logic Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hartani%20Kada">Hartani Kada</a>, <a href="https://publications.waset.org/abstracts/search?q=Merah%20Abdelkader"> Merah Abdelkader</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aiming at the high nonlinearities and unmatched uncertainties of the intelligent electric vehicles’ dynamic system, this paper presents a lateral motion control algorithm for intelligent electric vehicles with four in-wheel motors. A fuzzy logic procedure is presented and formulated to realize lateral control in lane change. The vehicle dynamics model and a desired target tracking model were established in this paper. A fuzzy logic controller was designed for integrated active front steering (AFS) and direct yaw moment control (DYC) in order to improve vehicle handling performance and stability, and a fuzzy controller for the automatic steering problem. The simulation results demonstrate the strong robustness and excellent tracking performance of the control algorithm that is proposed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title="fuzzy logic">fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=lateral%20control" title=" lateral control"> lateral control</a>, <a href="https://publications.waset.org/abstracts/search?q=AFS" title=" AFS"> AFS</a>, <a href="https://publications.waset.org/abstracts/search?q=DYC" title=" DYC"> DYC</a>, <a href="https://publications.waset.org/abstracts/search?q=electric%20car%20technology" title=" electric car technology"> electric car technology</a>, <a href="https://publications.waset.org/abstracts/search?q=longitudinal%20control" title=" longitudinal control"> longitudinal control</a>, <a href="https://publications.waset.org/abstracts/search?q=lateral%20motion" title=" lateral motion"> lateral motion</a> </p> <a href="https://publications.waset.org/abstracts/14474/lateral-control-of-electric-vehicle-based-on-fuzzy-logic-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14474.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">610</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">17057</span> Compensatory Neuro-Fuzzy Inference (CNFI) Controller for Bilateral Teleoperation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Mellah">R. Mellah</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Toumi"> R. Toumi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a new adaptive neuro-fuzzy controller equipped with compensatory fuzzy control (CNFI) in order to not only adjusts membership functions but also to optimize the adaptive reasoning by using a compensatory learning algorithm. The proposed control structure includes both CNFI controllers for which one is used to control in force the master robot and the second one for controlling in position the slave robot. The experimental results obtained, show a fairly high accuracy in terms of position and force tracking under free space motion and hard contact motion, what highlights the effectiveness of the proposed controllers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compensatory%20fuzzy" title="compensatory fuzzy">compensatory fuzzy</a>, <a href="https://publications.waset.org/abstracts/search?q=neuro-fuzzy" title=" neuro-fuzzy"> neuro-fuzzy</a>, <a href="https://publications.waset.org/abstracts/search?q=control%20adaptive" title=" control adaptive"> control adaptive</a>, <a href="https://publications.waset.org/abstracts/search?q=teleoperation" title=" teleoperation"> teleoperation</a> </p> <a href="https://publications.waset.org/abstracts/30465/compensatory-neuro-fuzzy-inference-cnfi-controller-for-bilateral-teleoperation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30465.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">324</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">17056</span> Comparison of Two Fuzzy Skyhook Control Strategies Applied to an Active Suspension</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Reginaldo%20Cardoso">Reginaldo Cardoso</a>, <a href="https://publications.waset.org/abstracts/search?q=Magno%20Enrique%20Mendoza%20Meza"> Magno Enrique Mendoza Meza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work focuses on simulation and comparison of two control skyhook techniques applied to a quarter-car of the active suspension. The objective is to provide comfort to the driver. The main idea of skyhook control is to imagine a damper connected to an imaginary sky; thus, the feedback is performed with the resultant force between the imaginary and the suspension damper. The first control technique is the Mandani fuzzy skyhook and the second control technique is a Takagi-Sugeno fuzzy skyhook controller, in the both controllers the inputs are the relative velocity between the two masses and the vehicle body velocity, the output of the Mandani fuzzy skyhook is the coefficient of imaginary damper viscous-friction and the Takagi-Sugeno fuzzy skyhook is the force. Finally, we compared the techniques. The Mandani fuzzy skyhook showed a more comfortable response to the driver, followed closely by the Takagi- Sugeno fuzzy skyhook. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=active%20suspention" title="active suspention">active suspention</a>, <a href="https://publications.waset.org/abstracts/search?q=Mandani" title=" Mandani"> Mandani</a>, <a href="https://publications.waset.org/abstracts/search?q=quarter-car" title=" quarter-car"> quarter-car</a>, <a href="https://publications.waset.org/abstracts/search?q=skyhook" title=" skyhook"> skyhook</a>, <a href="https://publications.waset.org/abstracts/search?q=Sugeno" title=" Sugeno"> Sugeno</a> </p> <a href="https://publications.waset.org/abstracts/32492/comparison-of-two-fuzzy-skyhook-control-strategies-applied-to-an-active-suspension" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32492.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">464</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">17055</span> A Type-2 Fuzzy Model for Link Prediction in Social Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mansoureh%20Naderipour">Mansoureh Naderipour</a>, <a href="https://publications.waset.org/abstracts/search?q=Susan%20Bastani"> Susan Bastani</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Fazel%20Zarandi"> Mohammad Fazel Zarandi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=social%20network" title="social network">social network</a>, <a href="https://publications.waset.org/abstracts/search?q=link%20prediction" title=" link prediction"> link prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=granular%20computing" title=" granular computing"> granular computing</a>, <a href="https://publications.waset.org/abstracts/search?q=type-2%20fuzzy%20sets" title=" type-2 fuzzy sets"> type-2 fuzzy sets</a> </p> <a href="https://publications.waset.org/abstracts/49749/a-type-2-fuzzy-model-for-link-prediction-in-social-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49749.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">326</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">17054</span> Liver Lesion Extraction with Fuzzy Thresholding in Contrast Enhanced Ultrasound Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abder-Rahman%20Ali">Abder-Rahman Ali</a>, <a href="https://publications.waset.org/abstracts/search?q=Ad%C3%A9la%C3%AFde%20Albouy-Kissi"> Adélaïde Albouy-Kissi</a>, <a href="https://publications.waset.org/abstracts/search?q=Manuel%20Grand-Brochier"> Manuel Grand-Brochier</a>, <a href="https://publications.waset.org/abstracts/search?q=Viviane%20Ladan-Marcus"> Viviane Ladan-Marcus</a>, <a href="https://publications.waset.org/abstracts/search?q=Christine%20Hoeffl"> Christine Hoeffl</a>, <a href="https://publications.waset.org/abstracts/search?q=Claude%20Marcus"> Claude Marcus</a>, <a href="https://publications.waset.org/abstracts/search?q=Antoine%20Vacavant"> Antoine Vacavant</a>, <a href="https://publications.waset.org/abstracts/search?q=Jean-Yves%20Boire"> Jean-Yves Boire</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=defuzzification" title="defuzzification">defuzzification</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20clustering" title=" fuzzy clustering"> fuzzy clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20segmentation" title=" image segmentation"> image segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=type-II%20fuzzy%20sets" title=" type-II fuzzy sets"> type-II fuzzy sets</a> </p> <a href="https://publications.waset.org/abstracts/32293/liver-lesion-extraction-with-fuzzy-thresholding-in-contrast-enhanced-ultrasound-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32293.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">485</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">17053</span> Robust H∞ State Feedback Control for Discrete Time T-S Fuzzy Systems Based on Fuzzy Lyapunov Function Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Walied%20Hanora">Walied Hanora</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the problem of robust state feedback H∞ for discrete time nonlinear system represented by Takagi-Sugeno fuzzy systems. Based on fuzzy lyapunov function, the condition ,which is represented in the form of Liner Matrix Inequalities (LMI), guarantees the H∞ performance of the T-S fuzzy system with uncertainties. By comparison with recent literature, this approach will be more relaxed condition. Finally, an example is given to illustrate the proposed result. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20lyapunov%20function" title="fuzzy lyapunov function">fuzzy lyapunov function</a>, <a href="https://publications.waset.org/abstracts/search?q=H%E2%88%9E%20control" title=" H∞ control "> H∞ control </a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20matrix%20inequalities" title=" linear matrix inequalities"> linear matrix inequalities</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20feedback" title=" state feedback"> state feedback</a>, <a href="https://publications.waset.org/abstracts/search?q=T-S%20fuzzy%20systems" title=" T-S fuzzy systems"> T-S fuzzy systems</a> </p> <a href="https://publications.waset.org/abstracts/58045/robust-h-state-feedback-control-for-discrete-time-t-s-fuzzy-systems-based-on-fuzzy-lyapunov-function-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58045.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">288</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">17052</span> Black Box Model and Evolutionary Fuzzy Control Methods of Coupled-Tank System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Yaman">S. Yaman</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Rostami"> S. Rostami </a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, a black box modeling of the coupled-tank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutionary computation method, genetic algorithm. All tuned controllers are applied to the fuzzy model of the coupled-tank experimental setup and analyzed under the different reference input values. According to the results, it is seen that function tuner method demonstrates better robust control performance and guarantees the closed loop stability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=function%20tuner%20method%20%28FTM%29" title="function tuner method (FTM)">function tuner method (FTM)</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20modeling" title=" fuzzy modeling"> fuzzy modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20PID%20controller" title=" fuzzy PID controller"> fuzzy PID controller</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm%20%28GA%29" title=" genetic algorithm (GA)"> genetic algorithm (GA)</a> </p> <a href="https://publications.waset.org/abstracts/50508/black-box-model-and-evolutionary-fuzzy-control-methods-of-coupled-tank-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50508.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">17051</span> Fuzzy Ideal Topological Spaces</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Koam">Ali Koam</a>, <a href="https://publications.waset.org/abstracts/search?q=Ismail%20Ibedou"> Ismail Ibedou</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20E.%20Abbas"> S. E. Abbas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, it is introduced the notion of r-fuzzy ideal separation axioms Tᵢi = 0; 1; 2 based on a fuzzy ideal I on a fuzzy topological space (X; τ). An r-fuzzy ideal connectedness related to the fuzzy ideal I is introduced which has relations with a previous r-fuzzy fuzzy connectedness. An r-fuzzy ideal compactness related to Ι is introduced which has also relations with many other types of fuzzy compactness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20ideal" title="fuzzy ideal">fuzzy ideal</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20separation%20axioms" title=" fuzzy separation axioms"> fuzzy separation axioms</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20compactness" title=" fuzzy compactness"> fuzzy compactness</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20connectedness" title=" fuzzy connectedness"> fuzzy connectedness</a> </p> <a href="https://publications.waset.org/abstracts/101746/fuzzy-ideal-topological-spaces" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/101746.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">17050</span> H∞ Takagi-Sugeno Fuzzy State-Derivative Feedback Control Design for Nonlinear Dynamic Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Kaewpraek">N. Kaewpraek</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20Assawinchaichote"> W. Assawinchaichote </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper considers an <em>H</em><sub>∞</sub> TS fuzzy state-derivative feedback controller for a class of nonlinear dynamical systems. A Takagi-Sugeno (TS) fuzzy model is used to approximate a class of nonlinear dynamical systems. Then, based on a linear matrix inequality (LMI) approach, we design an <em>H</em><sub>∞ </sub>TS fuzzy state-derivative feedback control law which guarantees <em>L</em><sub>2</sub>-gain of the mapping from the exogenous input noise to the regulated output to be less or equal to a prescribed value. We derive a sufficient condition such that the system with the fuzzy controller is asymptotically stable and <em>H</em><sub>∞</sub> performance is satisfied. Finally, we provide and simulate a numerical example is provided to illustrate the stability and the effectiveness of the proposed controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=h-infinity%20fuzzy%20control" title="h-infinity fuzzy control">h-infinity fuzzy control</a>, <a href="https://publications.waset.org/abstracts/search?q=an%20LMI%20approach" title=" an LMI approach"> an LMI approach</a>, <a href="https://publications.waset.org/abstracts/search?q=Takagi-Sugano%20%28TS%29%20fuzzy%20system" title=" Takagi-Sugano (TS) fuzzy system"> Takagi-Sugano (TS) fuzzy system</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20photovoltaic%20systems" title=" the photovoltaic systems"> the photovoltaic systems</a> </p> <a href="https://publications.waset.org/abstracts/37998/h-takagi-sugeno-fuzzy-state-derivative-feedback-control-design-for-nonlinear-dynamic-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37998.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">384</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">17049</span> Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Gherbi">S. Gherbi</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Bouchareb"> F. Bouchareb</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper deals with the novel intelligent bio-inspired control strategies, it presents a novel approach based on an optimal fuzzy immune PID parameters tuning, it is a combination of a PID controller, inspired by the human immune mechanism with fuzzy logic. Such controller offers more possibilities to deal with the delayed systems control difficulties due to the delay term. Indeed, we use an optimization approach to tune the four parameters of the controller in addition to the fuzzy function; the obtained controller is implemented in a modified Smith predictor structure, which is well known that it is the most efficient to the control of delayed systems. The application of the presented approach to control a three tank delay system shows good performances and proves the efficiency of the method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=delayed%20systems" title="delayed systems">delayed systems</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20immune%20PID" title=" fuzzy immune PID"> fuzzy immune PID</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=Smith%20predictor" title=" Smith predictor"> Smith predictor</a> </p> <a href="https://publications.waset.org/abstracts/10235/optimal-tuning-of-a-fuzzy-immune-pid-parameters-to-control-a-delayed-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10235.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">433</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">17048</span> Control of Hybrid System Using Fuzzy Logic</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Faiza%20Mahi">Faiza Mahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Fatima%20Debbat"> Fatima Debbat</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Fay%C3%A7al%20Khelfi"> Mohamed Fayçal Khelfi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a control approach using Fuzzy Lo system. More precisely, the study focuses on the improvement of users service in terms of analysis and control of a transportation system their waiting times in the exchange platforms of passengers. Many studies have been developed in the literature for such problematic, and many control tools are proposed. In this paper we focus on the use of fuzzy logic technique to control the system during its evolution in order to minimize the arrival gap of connected transportation means at the exchange points of passengers. An example of illustration is worked out and the obtained results are reported. an important area of research is the modeling and simulation ordering system. We describe an approach to analysis using Fuzzy Logic. The hybrid simulator developed in toolbox Matlab consists calculation of waiting time transportation mode. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fuzzy%20logic" title="Fuzzy logic">Fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=Hybrid%20system" title=" Hybrid system"> Hybrid system</a>, <a href="https://publications.waset.org/abstracts/search?q=Waiting%20Time" title=" Waiting Time"> Waiting Time</a>, <a href="https://publications.waset.org/abstracts/search?q=Transportation%20system" title=" Transportation system"> Transportation system</a>, <a href="https://publications.waset.org/abstracts/search?q=Control" title=" Control"> Control</a> </p> <a href="https://publications.waset.org/abstracts/22406/control-of-hybrid-system-using-fuzzy-logic" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/22406.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">555</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">17047</span> Enhancement of MIMO H₂S Gas Sweetening Separator Tower Using Fuzzy Logic Controller Array </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20M.%20A.%20S.%20Mahmoud">Muhammad M. A. S. Mahmoud</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Natural gas sweetening process is a controlled process that must be done at maximum efficiency and with the highest quality. In this work, due to complexity and non-linearity of the process, the H₂S gas separation and the intelligent fuzzy controller, which is used to enhance the process, are simulated in MATLAB – Simulink. The new design of fuzzy control for Gas Separator is discussed in this paper. The design is based on the utilization of linear state-estimation to generate the internal knowledge-base that stores input-output pairs. The obtained input/output pairs are then used to design a feedback fuzzy controller. The proposed closed-loop fuzzy control system maintains the system asymptotically-stability while it enhances the system time response to achieve better control of the concentration of the output gas from the tower. Simulation studies are carried out to illustrate the Gas Separator system performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gas%20separator" title="gas separator">gas separator</a>, <a href="https://publications.waset.org/abstracts/search?q=gas%20sweetening" title=" gas sweetening"> gas sweetening</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20controller" title=" intelligent controller"> intelligent controller</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20control" title=" fuzzy control"> fuzzy control</a> </p> <a href="https://publications.waset.org/abstracts/36514/enhancement-of-mimo-h2s-gas-sweetening-separator-tower-using-fuzzy-logic-controller-array" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36514.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">471</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">17046</span> Implementation and Design of Fuzzy Controller for High Performance Dc-Dc Boost Converters</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 discusses the implementation and design of both linear PI and fuzzy controllers for DC-DC boost converters. Design of PI controllers is based on temporal response of closed-loop converters, while fuzzy controllers design is based on heuristic knowledge of boost converters. Linear controller implementation is quite straightforward relying on mathematical models, while fuzzy controller implementation employs one or more artificial intelligences techniques. Comparison between these boost controllers is made in design aspect. Experimental results show that the proposed fuzzy controller system is robust against input voltage and load resistance changing and in respect of start-up transient. Results indicate that fuzzy controller can achieve best control performance concerning faster transient response, steady-state response good stability and accuracy under different operating conditions. Fuzzy controller is more suitable to control boost converters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=boost%20DC-DC%20converter" title="boost DC-DC converter">boost DC-DC converter</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy" title=" fuzzy"> fuzzy</a>, <a href="https://publications.waset.org/abstracts/search?q=PI%20controllers" title=" PI controllers"> PI controllers</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20electronics%20and%20control%20system" title=" power electronics and control system "> power electronics and control system </a> </p> <a href="https://publications.waset.org/abstracts/25094/implementation-and-design-of-fuzzy-controller-for-high-performance-dc-dc-boost-converters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25094.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">475</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">17045</span> Application of Fuzzy Logic in Voltage Regulation of Radial Feeder with Distributed Generators</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anubhav%20Shrivastava">Anubhav Shrivastava</a>, <a href="https://publications.waset.org/abstracts/search?q=Lakshya%20Bhat"> Lakshya Bhat</a>, <a href="https://publications.waset.org/abstracts/search?q=Shivarudraswamy"> Shivarudraswamy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Distributed Generation is the need of the hour. With current advancements in the DG technology, there are some major issues that need to be tackled in order to make this method of generation of energy more efficient and feasible. Among other problems, the control in voltage is the major issue that needs to be addressed. This paper focuses on control of voltage using reactive power control of DGs with the help of fuzzy logic. The membership functions have been defined accordingly and the control of the system is achieved. Finally, with the help of simulation results in Matlab, the control of voltage within the tolerance limit set (+/- 5%) is achieved. The voltage waveform graphs for the IEEE 14 bus system are obtained by using simple algorithm with MATLAB and then with fuzzy logic for 14 bus system. The goal of this project was to control the voltage within limits by controlling the reactive power of the DG using fuzzy logic. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distributed%20generation" title="distributed generation">distributed generation</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=matlab" title=" matlab"> matlab</a>, <a href="https://publications.waset.org/abstracts/search?q=newton%20raphson" title=" newton raphson"> newton raphson</a>, <a href="https://publications.waset.org/abstracts/search?q=IEEE%2014%20bus" title=" IEEE 14 bus"> IEEE 14 bus</a>, <a href="https://publications.waset.org/abstracts/search?q=voltage%20regulation" title=" voltage regulation"> voltage regulation</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20network" title=" radial network"> radial network</a> </p> <a href="https://publications.waset.org/abstracts/31759/application-of-fuzzy-logic-in-voltage-regulation-of-radial-feeder-with-distributed-generators" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31759.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">637</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">17044</span> Fuzzy Based Stabilizer Control System for Quad-Rotor</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20G.%20Sampath">B. G. Sampath</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20C.%20R.%20Perera"> K. C. R. Perera</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20A.%20S.%20I.%20Wijesuriya"> W. A. S. I. Wijesuriya</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20P.%20C.%20Dassanayake"> V. P. C. Dassanayake</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper the design, development and testing of a stabilizer control system for a Quad-rotor is presented which is focused on the maneuverability. The mechanical design is performed along with the design of the controlling algorithm which is devised using fuzzy logic controller. The inputs for the system are the angular positions and angular rates of the Quad-Rotor relative to three axes. Then the output data is filtered from an accelerometer and a gyroscope through a Kalman filter. In the development of the stability controlling system Mandani Fuzzy Model is incorporated. The results prove that the fuzzy based stabilizer control system is superior in high dynamic disturbances compared to the traditional systems which use PID integrated stabilizer control systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20stabilizer" title="fuzzy stabilizer">fuzzy stabilizer</a>, <a href="https://publications.waset.org/abstracts/search?q=maneuverability" title=" maneuverability"> maneuverability</a>, <a href="https://publications.waset.org/abstracts/search?q=PID" title=" PID"> PID</a>, <a href="https://publications.waset.org/abstracts/search?q=quad-rotor" title=" quad-rotor"> quad-rotor</a> </p> <a href="https://publications.waset.org/abstracts/3960/fuzzy-based-stabilizer-control-system-for-quad-rotor" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3960.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 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