Application of self-tuning fuzzy PID controller on industrial hydraulic acuator using system identification approach

Application of self-tuning fuzzy PID controller on industrial hydraulic acuator using system identification approach

In this project, Self Tuning Fuzzy (STF) PID controller is developed to improve the performance of the electro-hydraulic actuator. The controller is designed based on the mathematical model of the system which is estimated by using System Identification technique. The model is performed in linear di...

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Main Author: Yousefi, Rozbeh
Format: Thesis
Published: 2010
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spelling my-utm-ep.264132017-08-24T00:19:49Z Application of self-tuning fuzzy PID controller on industrial hydraulic acuator using system identification approach 2010 Yousefi, Rozbeh Unspecified In this project, Self Tuning Fuzzy (STF) PID controller is developed to improve the performance of the electro-hydraulic actuator. The controller is designed based on the mathematical model of the system which is estimated by using System Identification technique. The model is performed in linear discrete model to obtain a discrete transfer function for the system. Estimation of parameters model are done by using System Identification Toolbox in Matlab. Data for model estimation is taken from an experimental works. Fuzzy logic is used to tune each parameter of PID controller. Through simulation in Matlab by selecting appropriate fuzzy rules, STF are designed to tune the parameters Kp, Ki and Kd of the PID controller. It is observed that the performance based on time response of the hydraulic system has improved significantly compare to conventional PID controller. 2010 Thesis http://eprints.utm.my/id/eprint/26413/ http://libraryopac.utm.my/client/en_AU/main/search/results?qu=Application+of+self-tuning+fuzzy+PID+controller+on+industrial+hydraulic+acuator+using+system+identification+approach&te= masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
topic Unspecified
spellingShingle Unspecified
Yousefi, Rozbeh
Application of self-tuning fuzzy PID controller on industrial hydraulic acuator using system identification approach
description In this project, Self Tuning Fuzzy (STF) PID controller is developed to improve the performance of the electro-hydraulic actuator. The controller is designed based on the mathematical model of the system which is estimated by using System Identification technique. The model is performed in linear discrete model to obtain a discrete transfer function for the system. Estimation of parameters model are done by using System Identification Toolbox in Matlab. Data for model estimation is taken from an experimental works. Fuzzy logic is used to tune each parameter of PID controller. Through simulation in Matlab by selecting appropriate fuzzy rules, STF are designed to tune the parameters Kp, Ki and Kd of the PID controller. It is observed that the performance based on time response of the hydraulic system has improved significantly compare to conventional PID controller.
format Thesis
qualification_level Master's degree
author Yousefi, Rozbeh
author_facet Yousefi, Rozbeh
author_sort Yousefi, Rozbeh
title Application of self-tuning fuzzy PID controller on industrial hydraulic acuator using system identification approach
title_short Application of self-tuning fuzzy PID controller on industrial hydraulic acuator using system identification approach
title_full Application of self-tuning fuzzy PID controller on industrial hydraulic acuator using system identification approach
title_fullStr Application of self-tuning fuzzy PID controller on industrial hydraulic acuator using system identification approach
title_full_unstemmed Application of self-tuning fuzzy PID controller on industrial hydraulic acuator using system identification approach
title_sort application of self-tuning fuzzy pid controller on industrial hydraulic acuator using system identification approach
granting_institution Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department Faculty of Electrical Engineering
publishDate 2010
_version_ 1747815470385332224

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