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fuzzy PI controller</title> <meta name="description" content="Search results for: adaptive fuzzy PI controller"> <meta name="keywords" content="adaptive fuzzy PI controller"> <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 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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="adaptive fuzzy PI controller"> <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> 2253</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: adaptive fuzzy PI controller</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2253</span> Design and Simulation of Unified Power Quality Conditioner based on Adaptive Fuzzy PI Controller</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Brahim%20Ferdi">Brahim Ferdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Samira%20Dib"> Samira Dib</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The unified power quality conditioner (UPQC), a combination of shunt and series active power filter, is one of the best solutions towards the mitigation of voltage and current harmonics problems in distribution power system. PI controller is very common in the control of UPQC. However, one disadvantage of this conventional controller is the difficulty in tuning its gains (Kp and Ki). To overcome this problem, an adaptive fuzzy logic PI controller is proposed. The controller is composed of fuzzy controller and PI controller. According to the error and error rate of the control system and fuzzy control rules, the fuzzy controller can online adjust the two gains of the PI controller to get better performance of UPQC. Simulations using MATLAB/SIMULINK are carried out to verify the performance of the proposed controller. The results show that the proposed controller has fast dynamic response and high accuracy of tracking the current and voltage references. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20fuzzy%20PI%20controller" title="adaptive fuzzy PI controller">adaptive fuzzy PI controller</a>, <a href="https://publications.waset.org/abstracts/search?q=current%20harmonics" title=" current harmonics"> current harmonics</a>, <a href="https://publications.waset.org/abstracts/search?q=PI%20controller" title=" PI controller"> PI controller</a>, <a href="https://publications.waset.org/abstracts/search?q=voltage%20harmonics" title=" voltage harmonics"> voltage harmonics</a>, <a href="https://publications.waset.org/abstracts/search?q=UPQC" title=" UPQC"> UPQC</a> </p> <a href="https://publications.waset.org/abstracts/16996/design-and-simulation-of-unified-power-quality-conditioner-based-on-adaptive-fuzzy-pi-controller" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16996.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">556</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">2252</span> A Development of Holonomic Mobile Robot Using Fuzzy Multi-Layered Controller</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seungwoo%20Kim">Seungwoo Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Yeongcheol%20Cho"> Yeongcheol Cho</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a holonomic mobile robot is designed in omnidirectional wheels and an adaptive fuzzy controller is presented for its precise trajectories. A kind of adaptive controller based on fuzzy multi-layered algorithm is used to solve the big parametric uncertainty of motor-controlled dynamic system of 3-wheels omnidirectional mobile robot. The system parameters such as a tracking force are so time-varying due to the kinematic structure of omnidirectional wheels. The fuzzy adaptive control method is able to solve the problems of classical adaptive controller and conventional fuzzy adaptive controllers. The basic idea of new adaptive control scheme is that an adaptive controller can be constructed with parallel combination of robust controllers. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good performance of a holonomic mobile robot is confirmed through live tests of the tracking control task. <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=fuzzy%20multi-layered%20controller" title=" fuzzy multi-layered controller"> fuzzy multi-layered controller</a>, <a href="https://publications.waset.org/abstracts/search?q=holonomic%20mobile%20robot" title=" holonomic mobile robot"> holonomic mobile robot</a>, <a href="https://publications.waset.org/abstracts/search?q=omnidirectional%20wheels" title=" omnidirectional wheels"> omnidirectional wheels</a>, <a href="https://publications.waset.org/abstracts/search?q=robustness%20and%20stability." title=" robustness and stability. "> robustness and stability. </a> </p> <a href="https://publications.waset.org/abstracts/43824/a-development-of-holonomic-mobile-robot-using-fuzzy-multi-layered-controller" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43824.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">359</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">2251</span> Active Power Control of PEM Fuel Cell System Power Generation Using Adaptive Neuro-Fuzzy Controller</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khaled%20Mammar">Khaled Mammar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an application of adaptive neuro-fuzzy controller for PEM fuel cell system. The model proposed for control include a fuel cell stack model, reformer model and DC/AC inverter model. Furthermore, a Fuzzy Logic (FLC) and adaptive neuro-fuzzy controllers are used to control the active power of PEM fuel cell system. The controllers modify the hydrogen flow feedback from the terminal load. The validity of the controller is verified when the fuel cell system model is used in conjunction with the ANFIS controller to predict the response of the active power. Simulation results confirmed the high-performance capability of the neuo-fuzzy to control power generation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuel%20cell" title="fuel cell">fuel cell</a>, <a href="https://publications.waset.org/abstracts/search?q=PEMFC" title=" PEMFC"> PEMFC</a>, <a href="https://publications.waset.org/abstracts/search?q=modeling" title=" modeling"> modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=Fuzzy%20Logic%20Controller" title=" Fuzzy Logic Controller"> Fuzzy Logic Controller</a>, <a href="https://publications.waset.org/abstracts/search?q=FLC" title=" FLC"> FLC</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20neuro-fuzzy%20controller" title=" adaptive neuro-fuzzy controller"> adaptive neuro-fuzzy controller</a>, <a href="https://publications.waset.org/abstracts/search?q=ANFIS" title=" ANFIS"> ANFIS</a> </p> <a href="https://publications.waset.org/abstracts/30876/active-power-control-of-pem-fuel-cell-system-power-generation-using-adaptive-neuro-fuzzy-controller" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30876.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">459</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">2250</span> Fault-Tolerant Fuzzy Gain-Adaptive PID Control for a 2 DOF Helicopter, TRMS System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abderrahmen%20Bouguerra">Abderrahmen Bouguerra</a>, <a href="https://publications.waset.org/abstracts/search?q=Kamel%20Kara"> Kamel Kara</a>, <a href="https://publications.waset.org/abstracts/search?q=Djamel%20Saigaa"> Djamel Saigaa</a>, <a href="https://publications.waset.org/abstracts/search?q=Samir%20Zeghlache"> Samir Zeghlache</a>, <a href="https://publications.waset.org/abstracts/search?q=Keltoum%20Loukal"> Keltoum Loukal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a Fault-Tolerant control of 2 DOF Helicopter (TRMS System) Based on Fuzzy Gain-Adaptive PID is presented. In particular, the introduction part of the paper presents a Fault-Tolerant Control (FTC), the first part of this paper presents a description of the mathematical model of TRMS, an adaptive PID controller is proposed for fault-tolerant control of a TRMS helicopter system in the presence of actuator faults, A fuzzy inference scheme is used to tune in real-time the controller gains, The proposed adaptive PID controller is compared with the conventional PID. The obtained results show the effectiveness of the proposed method. <p class="card-text"><strong>Keywords:</strong> <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=gain-adaptive%20PID" title=" gain-adaptive PID"> gain-adaptive PID</a>, <a href="https://publications.waset.org/abstracts/search?q=helicopter%20model" title=" helicopter model"> helicopter model</a>, <a href="https://publications.waset.org/abstracts/search?q=PID%20control" title=" PID control"> PID control</a>, <a href="https://publications.waset.org/abstracts/search?q=TRMS%20system" title=" TRMS system"> TRMS system</a> </p> <a href="https://publications.waset.org/abstracts/21698/fault-tolerant-fuzzy-gain-adaptive-pid-control-for-a-2-dof-helicopter-trms-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21698.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">2249</span> Particle Swarm Optimization Based Vibration Suppression of a Piezoelectric Actuator Using Adaptive Fuzzy Sliding Mode Controller</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jin-Siang%20Shaw">Jin-Siang Shaw</a>, <a href="https://publications.waset.org/abstracts/search?q=Patricia%20Moya%20Caceres"> Patricia Moya Caceres</a>, <a href="https://publications.waset.org/abstracts/search?q=Sheng-Xiang%20Xu"> Sheng-Xiang Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper aims to integrate the particle swarm optimization (PSO) method with the adaptive fuzzy sliding mode controller (AFSMC) to achieve vibration attenuation in a piezoelectric actuator subject to base excitation. The piezoelectric actuator is a complicated system made of ferroelectric materials and its performance can be affected by nonlinear hysteresis loop and unknown system parameters and external disturbances. In this study, an adaptive fuzzy sliding mode controller is proposed for the vibration control of the system, because the fuzzy sliding mode controller is designed to tackle the unknown parameters and external disturbance of the system, and the adaptive algorithm is aimed for fine-tuning this controller for error converging purpose. Particle swarm optimization method is used in order to find the optimal controller parameters for the piezoelectric actuator. PSO starts with a population of random possible solutions, called particles. The particles move through the search space with dynamically adjusted speed and direction that change according to their historical behavior, allowing the values of the particles to quickly converge towards the best solutions for the proposed problem. In this paper, an initial set of controller parameters is applied to the piezoelectric actuator which is subject to resonant base excitation with large amplitude vibration. The resulting vibration suppression is about 50%. Then PSO is applied to search for an optimal controller in the neighborhood of this initial controller. The performance of the optimal fuzzy sliding mode controller found by PSO indeed improves up to 97.8% vibration attenuation. Finally, adaptive version of fuzzy sliding mode controller is adopted for further improving vibration suppression. Simulation result verifies the performance of the adaptive controller with 99.98% vibration reduction. Namely the vibration of the piezoelectric actuator subject to resonant base excitation can be completely annihilated using this PSO based adaptive fuzzy sliding mode controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20fuzzy%20sliding%20mode%20controller" title="adaptive fuzzy sliding mode controller">adaptive fuzzy sliding mode controller</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=piezoelectric%20actuator" title=" piezoelectric actuator"> piezoelectric actuator</a>, <a href="https://publications.waset.org/abstracts/search?q=vibration%20suppression" title=" vibration suppression"> vibration suppression</a> </p> <a href="https://publications.waset.org/abstracts/99760/particle-swarm-optimization-based-vibration-suppression-of-a-piezoelectric-actuator-using-adaptive-fuzzy-sliding-mode-controller" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99760.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">2248</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">2247</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">2246</span> Optimization of the Control Scheme for Human Extremity Exoskeleton</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yang%20Li">Yang Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaorong%20Guan"> Xiaorong Guan</a>, <a href="https://publications.waset.org/abstracts/search?q=Cheng%20Xu"> Cheng Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to design a suitable control scheme for human extremity exoskeleton, the interaction force control scheme with traditional PI controller was presented, and the simulation study of the electromechanical system of the human extremity exoskeleton was carried out by using a MATLAB/Simulink module. By analyzing the simulation calculation results, it was shown that the traditional PI controller is not very suitable for every movement speed of human body. So, at last the fuzzy self-adaptive PI controller was presented to solve this problem. Eventually, the superiority and feasibility of the fuzzy self-adaptive PI controller was proved by the simulation results and experimental results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=human%20extremity%20exoskeleton" title="human extremity exoskeleton">human extremity exoskeleton</a>, <a href="https://publications.waset.org/abstracts/search?q=interaction%20force%20control%20scheme" title=" interaction force control scheme"> interaction force control scheme</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation%20study" title=" simulation study"> simulation study</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20self-adaptive%20pi%20controller" title=" fuzzy self-adaptive pi controller"> fuzzy self-adaptive pi controller</a>, <a href="https://publications.waset.org/abstracts/search?q=man-machine%20coordinated%20walking" title=" man-machine coordinated walking"> man-machine coordinated walking</a>, <a href="https://publications.waset.org/abstracts/search?q=bear%20payload" title=" bear payload"> bear payload</a> </p> <a href="https://publications.waset.org/abstracts/53441/optimization-of-the-control-scheme-for-human-extremity-exoskeleton" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53441.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">362</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">2245</span> Speed Control of Hybrid Stepper Motor by Using Adaptive Neuro-Fuzzy Controller</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Talha%20Ali%20Khan">Talha Ali Khan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an adaptive neuro-fuzzy interference system (ANFIS), which is applied to a hybrid stepper motor (HSM) to regulate its speed. The dynamic response of the HSM with the ANFIS controller is studied during the starting process and under different load disturbance. The effectiveness of the proposed controller is compared with that of the conventional PI controller. The proposed method solves the problem of nonlinearities and load changes of the HSM drives. The proposed controller ensures fast and precise dynamic response with an excellent steady state performance. Matlab/Simulink program is used for this dynamic simulation study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stepper%20motor" title="stepper motor">stepper motor</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid" title=" hybrid"> hybrid</a>, <a href="https://publications.waset.org/abstracts/search?q=ANFIS" title=" ANFIS"> ANFIS</a>, <a href="https://publications.waset.org/abstracts/search?q=speed%20control" title=" speed control"> speed control</a> </p> <a href="https://publications.waset.org/abstracts/15484/speed-control-of-hybrid-stepper-motor-by-using-adaptive-neuro-fuzzy-controller" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15484.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">551</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">2244</span> Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.-W.%20Tsai">P.-W. Tsai</a>, <a href="https://publications.waset.org/abstracts/search?q=C.-Y.%20Chen"> C.-Y. Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=C.-W.%20Chen"> C.-W. Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20fuzzy%20sliding%20mode%20control" title="adaptive fuzzy sliding mode control">adaptive fuzzy sliding mode control</a>, <a href="https://publications.waset.org/abstracts/search?q=Lyapunov%20direct%20method" title=" Lyapunov direct method"> Lyapunov direct method</a>, <a href="https://publications.waset.org/abstracts/search?q=swarm%20intelligence" title=" swarm intelligence"> swarm intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=evolved%20bat%20algorithm" title=" evolved bat algorithm"> evolved bat algorithm</a> </p> <a href="https://publications.waset.org/abstracts/11231/evolved-bat-algorithm-based-adaptive-fuzzy-sliding-mode-control-with-lmi-criterion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11231.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">445</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">2243</span> Designing Intelligent Adaptive Controller for Nonlinear Pendulum Dynamical System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Ghasemi">R. Ghasemi</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20R.%20Rahimi%20Khoygani"> M. R. Rahimi Khoygani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes the designing direct adaptive neural controller to apply for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) neural adaptive controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are importance of this paper. The simulation results show the promising performance of the proposed controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20neural%20controller" title="adaptive neural controller">adaptive neural controller</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20dynamical" title=" nonlinear dynamical"> nonlinear dynamical</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=RBF" title=" RBF"> RBF</a>, <a href="https://publications.waset.org/abstracts/search?q=driven%20pendulum" title=" driven pendulum"> driven pendulum</a>, <a href="https://publications.waset.org/abstracts/search?q=position%20control" title=" position control "> position control </a> </p> <a href="https://publications.waset.org/abstracts/13745/designing-intelligent-adaptive-controller-for-nonlinear-pendulum-dynamical-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13745.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">482</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">2242</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">2241</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">2240</span> Performance Comparisons between PID and Adaptive PID Controllers for Travel Angle Control of a Bench-Top Helicopter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Mansor">H. Mansor</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20B.%20Mohd-Noor"> S. B. Mohd-Noor</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20S.%20Gunawan"> T. S. Gunawan</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Khan"> S. Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20I.%20Othman"> N. I. Othman</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Tazali"> N. Tazali</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20B.%20Islam"> R. B. Islam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper provides a comparative study on the performances of standard PID and adaptive PID controllers tested on travel angle of a 3-Degree-of-Freedom (3-DOF) Quanser bench-top helicopter. Quanser, a well-known manufacturer of educational bench-top helicopter has developed Proportional Integration Derivative (PID) controller with Linear Quadratic Regulator (LQR) for all travel, pitch and yaw angle of the bench-top helicopter. The performance of the PID controller is relatively good; however its performance could also be improved if the controller is combined with adaptive element. The objective of this research is to design adaptive PID controller and then compare the performances of the adaptive PID with the standard PID. The controller design and test is focused on travel angle control only. Adaptive method used in this project is self-tuning controller, which controller’s parameters are updated online. Two adaptive algorithms those are pole-placement and deadbeat have been chosen as the method to achieve optimal controller’s parameters. Performance comparisons have shown that the adaptive (deadbeat) PID controller has produced more desirable performance compared to standard PID and adaptive (pole-placement). The adaptive (deadbeat) PID controller attained very fast settling time (5 seconds) and very small percentage of overshoot (5% to 7.5%) for 10° to 30° step change of travel angle. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20control" title="adaptive control">adaptive control</a>, <a href="https://publications.waset.org/abstracts/search?q=deadbeat" title=" deadbeat"> deadbeat</a>, <a href="https://publications.waset.org/abstracts/search?q=pole-placement" title=" pole-placement"> pole-placement</a>, <a href="https://publications.waset.org/abstracts/search?q=bench-top%20helicopter" title=" bench-top helicopter"> bench-top helicopter</a>, <a href="https://publications.waset.org/abstracts/search?q=self-tuning%20control" title=" self-tuning control"> self-tuning control</a> </p> <a href="https://publications.waset.org/abstracts/15094/performance-comparisons-between-pid-and-adaptive-pid-controllers-for-travel-angle-control-of-a-bench-top-helicopter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15094.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">501</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">2239</span> Maximum Power Point Tracking Using FLC Tuned with GA</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Amine%20Haraoubia">Mohamed Amine Haraoubia</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelaziz%20Hamzaoui"> Abdelaziz Hamzaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Najib%20Essounbouli"> Najib Essounbouli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The pursuit of the MPPT has led to the development of many kinds of controllers, one of which is the Fuzzy Logic Controller, which has proven its worth. To further tune this controller this paper will discuss and analyze the use of Genetic Algorithms to tune the Fuzzy Logic Controller. It will provide an introduction to both systems, and test their compatibility and performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic%20controller" title="fuzzy logic controller">fuzzy logic controller</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=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20power%20point" title=" maximum power point"> maximum power point</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20power%20point%20tracking" title=" maximum power point tracking"> maximum power point tracking</a> </p> <a href="https://publications.waset.org/abstracts/7055/maximum-power-point-tracking-using-flc-tuned-with-ga" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7055.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">2238</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">2237</span> Improving Ride Comfort of a Bus Using Fuzzy Logic Controlled Suspension</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mujde%20Turkkan">Mujde Turkkan</a>, <a href="https://publications.waset.org/abstracts/search?q=Nurkan%20Yagiz"> Nurkan Yagiz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study an active controller is presented for vibration suppression of a full-bus model. The bus is modelled having seven degrees of freedom. Using the achieved model via Lagrange Equations the system equations of motion are derived. The suspensions of the bus model include air springs with two auxiliary chambers are used. Fuzzy logic controller is used to improve the ride comfort. The numerical results, verifies that the presented fuzzy logic controller improves the ride comfort. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ride%20comfort" title="ride comfort">ride comfort</a>, <a href="https://publications.waset.org/abstracts/search?q=air%20spring" title=" air spring"> air spring</a>, <a href="https://publications.waset.org/abstracts/search?q=bus" title=" bus"> bus</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic%20controller" title=" fuzzy logic controller"> fuzzy logic controller</a> </p> <a href="https://publications.waset.org/abstracts/3740/improving-ride-comfort-of-a-bus-using-fuzzy-logic-controlled-suspension" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3740.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">430</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">2236</span> Neural Adaptive Controller for a Class of Nonlinear Pendulum Dynamical System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Reza%20Rahimi%20Khoygani">Mohammad Reza Rahimi Khoygani</a>, <a href="https://publications.waset.org/abstracts/search?q=Reza%20Ghasemi"> Reza Ghasemi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, designing direct adaptive neural controller is applied for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) is used for the Neural network (NN). The adaptive neural controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are the merits of this paper. The promising performance of the proposed controllers investigates in simulation results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20control" title="adaptive control">adaptive control</a>, <a href="https://publications.waset.org/abstracts/search?q=pendulum%20dynamical%20system" title=" pendulum dynamical system"> pendulum dynamical system</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20control" title=" nonlinear control"> nonlinear control</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20neural%20controller" title=" adaptive neural controller"> adaptive neural controller</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20dynamical" title=" nonlinear dynamical"> nonlinear dynamical</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=RBF" title=" RBF"> RBF</a>, <a href="https://publications.waset.org/abstracts/search?q=driven%20pendulum" title=" driven pendulum"> driven pendulum</a>, <a href="https://publications.waset.org/abstracts/search?q=position%20control" title=" position control "> position control </a> </p> <a href="https://publications.waset.org/abstracts/13649/neural-adaptive-controller-for-a-class-of-nonlinear-pendulum-dynamical-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13649.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">670</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">2235</span> Maximum Power Point Tracking Using Fuzzy Logic Control for a Stand-Alone PV System with PI Controller for Battery Charging Based on Evolutionary Technique</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20A.%20Moustafa%20Hassan">Mohamed A. Moustafa Hassan</a>, <a href="https://publications.waset.org/abstracts/search?q=Omnia%20S%20.S.%20Hussian"> Omnia S .S. Hussian</a>, <a href="https://publications.waset.org/abstracts/search?q=Hany%20M.%20Elsaved"> Hany M. Elsaved</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper introduces the application of Fuzzy Logic Controller (FLC) to extract the Maximum Power Point Tracking (MPPT) from the PV panel. In addition, the proportional integral (PI) controller is used to be the strategy for battery charge control according to acceptable performance criteria. The parameters of the PI controller have been tuned via Modified Adaptive Accelerated Coefficient Particle Swarm Optimization (MAACPSO) technique. The simulation results, using MATLAB/Simulink tools, show that the FLC technique has advantages for use in the MPPT problem, as it provides a fast response under changes in environmental conditions such as radiation and temperature. In addition, the use of PI controller based on MAACPSO results in a good performance in terms of controlling battery charging with constant voltage and current to execute rapid charging. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=battery%20charging" title="battery charging">battery charging</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=maximum%20power%20point%20tracking" title=" maximum power point tracking"> maximum power point tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=PV%20system" title=" PV system"> PV system</a>, <a href="https://publications.waset.org/abstracts/search?q=PI%20controller" title=" PI controller"> PI controller</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20technique" title=" evolutionary technique"> evolutionary technique</a> </p> <a href="https://publications.waset.org/abstracts/109686/maximum-power-point-tracking-using-fuzzy-logic-control-for-a-stand-alone-pv-system-with-pi-controller-for-battery-charging-based-on-evolutionary-technique" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/109686.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">166</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">2234</span> An Observer-Based Direct Adaptive Fuzzy Sliding Control with Adjustable Membership Functions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alireza%20Gholami">Alireza Gholami</a>, <a href="https://publications.waset.org/abstracts/search?q=Amir%20H.%20D.%20Markazi"> Amir H. D. Markazi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, an observer-based direct adaptive fuzzy sliding mode (OAFSM) algorithm is proposed. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. The input connection matrix is used to combine the sliding surfaces of individual subsystems, and an adaptive fuzzy algorithm is used to estimate an equivalent sliding mode control input directly. The fuzzy membership functions, which were determined by time consuming try and error processes in previous works, are adjusted by adaptive algorithms. The other advantage of the proposed controller is that the input gain matrix is not limited to be diagonal, i.e. the plant could be over/under actuated provided that controllability and observability are preserved. An observer is constructed to directly estimate the state tracking error, and the nonlinear part of the observer is constructed by an adaptive fuzzy algorithm. The main advantage of the proposed observer is that, the measured outputs is not limited to the first entry of a canonical-form state vector. The closed-loop stability of the proposed method is proved using a Lyapunov-based approach. The proposed method is applied numerically on a multi-link robot manipulator, which verifies the performance of the closed-loop control. Moreover, the performance of the proposed algorithm is compared with some conventional control algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20algorithm" title="adaptive algorithm">adaptive algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20systems" title=" fuzzy systems"> fuzzy systems</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20functions" title=" membership functions"> membership functions</a>, <a href="https://publications.waset.org/abstracts/search?q=observer" title=" observer"> observer</a> </p> <a href="https://publications.waset.org/abstracts/81807/an-observer-based-direct-adaptive-fuzzy-sliding-control-with-adjustable-membership-functions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81807.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">206</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">2233</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">2232</span> Design and Implementation of a Fan Coil Unit Controller Based on the Duty Ratio Fuzzy Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Liang%20Zhao">Liang Zhao</a>, <a href="https://publications.waset.org/abstracts/search?q=Jili%20Zhang"> Jili Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Kai%20Li"> Kai Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A microcontroller-based fan coil unit (FCU) fuzzy controller is designed and implemented in this paper. The controller employs the concept of duty ratio on the electric valve control, which could make full use of the cooling and dehumidifying capacity of the FCU when the valve is off. The traditional control method and its limitations are analyzed. The hardware and software design processes are introduced in detail. The experimental results show that the proposed method is more energy efficient compared to the traditional controlling strategy. Furthermore, a more comfortable room condition could be achieved by the proposed method. The proposed low-cost FCU fuzzy controller deserves to be widely used in engineering applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fan%20coil%20unit" title="fan coil unit">fan coil unit</a>, <a href="https://publications.waset.org/abstracts/search?q=duty%20ratio" title=" duty ratio"> duty ratio</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=experiment" title=" experiment"> experiment</a> </p> <a href="https://publications.waset.org/abstracts/52767/design-and-implementation-of-a-fan-coil-unit-controller-based-on-the-duty-ratio-fuzzy-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52767.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">339</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">2231</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">2230</span> Multi-Agent Coverage Control with Bounded Gain Forgetting Composite Adaptive Controller</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mert%20Turanli">Mert Turanli</a>, <a href="https://publications.waset.org/abstracts/search?q=Hakan%20Temeltas"> Hakan Temeltas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20control" title="adaptive control">adaptive control</a>, <a href="https://publications.waset.org/abstracts/search?q=centroidal%20voronoi%20tessellations" title=" centroidal voronoi tessellations"> centroidal voronoi tessellations</a>, <a href="https://publications.waset.org/abstracts/search?q=composite%20adaptation" title=" composite adaptation"> composite adaptation</a>, <a href="https://publications.waset.org/abstracts/search?q=coordination" title=" coordination"> coordination</a>, <a href="https://publications.waset.org/abstracts/search?q=multi%20robots" title=" multi robots"> multi robots</a> </p> <a href="https://publications.waset.org/abstracts/57931/multi-agent-coverage-control-with-bounded-gain-forgetting-composite-adaptive-controller" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57931.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">348</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">2229</span> Fuzzy and Fuzzy-PI Controller for Rotor Speed of Gas Turbine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mandar%20Ghodekar">Mandar Ghodekar</a>, <a href="https://publications.waset.org/abstracts/search?q=Sharad%20Jadhav"> Sharad Jadhav</a>, <a href="https://publications.waset.org/abstracts/search?q=Sangram%20Jadhav"> Sangram Jadhav</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speed control of rotor during startup and under varying load conditions is one of the most difficult tasks of gas turbine operation. In this paper, power plant gas turbine (GE9001E) is considered for this purpose and fuzzy and fuzzy-PI rotor speed controllers are designed. The goal of the presented controllers is to keep the turbine rotor speed within predefined limits during startup condition as well as during operating condition. The fuzzy controller and fuzzy-PI controller are designed using Takagi-Sugeno method and Mamdani method, respectively. In applying the fuzzy-PI control to a gas-turbine plant, the tuning parameters (Kp and Ki) are modified online by fuzzy logic approach. Error and rate of change of error are inputs and change in fuel flow is output for both the controllers. Hence, rotor speed of gas turbine is controlled by modifying the fuel flow. The identified linear ARX model of gas turbine is considered while designing the controllers. For simulations, demand power is taken as disturbance input. It is assumed that inlet guide vane (IGV) position is fixed. In addition, the constraint on the fuel flow is taken into account. The performance of the presented controllers is compared with each other as well as with H∞ robust and MPC controllers for the same operating conditions in simulations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gas%20turbine" title="gas turbine">gas turbine</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=fuzzy%20PI%20controller" title=" fuzzy PI controller"> fuzzy PI controller</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20plant" title=" power plant"> power plant</a> </p> <a href="https://publications.waset.org/abstracts/41546/fuzzy-and-fuzzy-pi-controller-for-rotor-speed-of-gas-turbine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41546.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">334</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">2228</span> Recursive Parametric Identification of a Doubly Fed Induction Generator-Based Wind Turbine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20El%20Kachani">A. El Kachani</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Chakir"> E. Chakir</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Ait%20Laachir"> A. Ait Laachir</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Niaaniaa"> A. Niaaniaa</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20Zerouaoui"> J. Zerouaoui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This document presents an adaptive controller based on recursive parametric identification applied to a wind turbine based on the doubly-fed induction machine (DFIG), to compensate the faults and guarantee efficient of the DFIG. The proposed adaptive controller is based on the recursive least square algorithm which considers that the best estimator for the vector parameter is the vector x minimizing a quadratic criterion. Furthermore, this method can improve the rapidity and precision of the controller based on a model. The proposed controller is validated via simulation on a 5.5 kW DFIG-based wind turbine. The results obtained seem to be good. In addition, they show the advantages of an adaptive controller based on recursive least square algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20controller" title="adaptive controller">adaptive controller</a>, <a href="https://publications.waset.org/abstracts/search?q=recursive%20least%20squares%20algorithm" title=" recursive least squares algorithm"> recursive least squares algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20turbine" title=" wind turbine"> wind turbine</a>, <a href="https://publications.waset.org/abstracts/search?q=doubly%20fed%20induction%20generator" title=" doubly fed induction generator"> doubly fed induction generator</a> </p> <a href="https://publications.waset.org/abstracts/47239/recursive-parametric-identification-of-a-doubly-fed-induction-generator-based-wind-turbine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47239.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">2227</span> Fuzzy Sliding Mode Control of a Flexible Structure for Vibration Suppression Using MFC Actuator</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jinsiang%20Shaw">Jinsiang Shaw</a>, <a href="https://publications.waset.org/abstracts/search?q=Shih-Chieh%20Tseng"> Shih-Chieh Tseng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Active vibration control is good for low frequency excitation, with advantages of light weight and adaptability. This paper use a macro-fiber composite (MFC) actuator for vibration suppression in a cantilevered beam due to its higher output force to suppress the disturbance. A fuzzy sliding mode controller is developed and applied to this system. Experimental results illustrate that the controller and MFC actuator are very effective in attenuating the structural vibration near the first resonant freuqency. Furthermore, this controller is shown to outperform the traditional skyhook controller, with nearly 90% of the vibration suppressed at the first resonant frequency of the structure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fuzzy%20sliding%20mode%20controller" title="Fuzzy sliding mode controller">Fuzzy sliding mode controller</a>, <a href="https://publications.waset.org/abstracts/search?q=macro-fiber-composite%20actuator" title=" macro-fiber-composite actuator"> macro-fiber-composite actuator</a>, <a href="https://publications.waset.org/abstracts/search?q=skyhook%20controller" title=" skyhook controller"> skyhook controller</a>, <a href="https://publications.waset.org/abstracts/search?q=vibration%20suppression" title=" vibration suppression"> vibration suppression</a> </p> <a href="https://publications.waset.org/abstracts/25138/fuzzy-sliding-mode-control-of-a-flexible-structure-for-vibration-suppression-using-mfc-actuator" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25138.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">403</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">2226</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">2225</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">2224</span> Self-Tuning Dead-Beat PD Controller for Pitch Angle Control of a Bench-Top Helicopter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Mansor">H. Mansor</a>, <a href="https://publications.waset.org/abstracts/search?q=S.B.%20Mohd-Noor"> S.B. Mohd-Noor</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20I.%20Othman"> N. I. Othman</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Tazali"> N. Tazali</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20I.%20Boby"> R. I. Boby</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an improved robust Proportional Derivative controller for a 3-Degree-of-Freedom (3-DOF) bench-top helicopter by using adaptive methodology. Bench-top helicopter is a laboratory scale helicopter used for experimental purposes which is widely used in teaching laboratory and research. Proportional Derivative controller has been developed for a 3-DOF bench-top helicopter by Quanser. Experiments showed that the transient response of designed PD controller has very large steady state error i.e., 50%, which is very serious. The objective of this research is to improve the performance of existing pitch angle control of PD controller on the bench-top helicopter by integration of PD controller with adaptive controller. Usually standard adaptive controller will produce zero steady state error; however response time to reach desired set point is large. Therefore, this paper proposed an adaptive with deadbeat algorithm to overcome the limitations. The output response that is fast, robust and updated online is expected. Performance comparisons have been performed between the proposed self-tuning deadbeat PD controller and standard PD controller. The efficiency of the self-tuning dead beat controller has been proven from the tests results in terms of faster settling time, zero steady state error and capability of the controller to be updated online. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20control" title="adaptive control">adaptive control</a>, <a href="https://publications.waset.org/abstracts/search?q=deadbeat%20control" title=" deadbeat control"> deadbeat control</a>, <a href="https://publications.waset.org/abstracts/search?q=bench-top%20helicopter" title=" bench-top helicopter"> bench-top helicopter</a>, <a href="https://publications.waset.org/abstracts/search?q=self-tuning%20control" title=" self-tuning control"> self-tuning control</a> </p> <a href="https://publications.waset.org/abstracts/10581/self-tuning-dead-beat-pd-controller-for-pitch-angle-control-of-a-bench-top-helicopter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10581.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> <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=adaptive%20fuzzy%20PI%20controller&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=adaptive%20fuzzy%20PI%20controller&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=adaptive%20fuzzy%20PI%20controller&page=4">4</a></li> <li class="page-item"><a class="page-link" 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