Optimization of Self-Tuning Fuzzy PI-PD Controller Using Genetic Algorithm

 




 

Lee, Khai Sheng (2018) Optimization of Self-Tuning Fuzzy PI-PD Controller Using Genetic Algorithm. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

Fuzzy logic controller is widely applied on research purpose in recent year. This is because fuzzy logic controller can improve the performance of a system of the engineering application. Optimization process is used in the fuzzy logic controller to improve the performance of the system. Therefore, the optimization method is important to be determine for optimize the fuzzy logic controller. The research had set an aim to investigate the optimization of self-tuning fuzzy PI-PD controller. There are a lots of optimization method to optimize the fuzzy logic controller. Genetic Algorithm is the selected method for the research as it is the basic algorithm of the optimization because it required some background of the genetic algorithm to apply on the optimization. The result of self-tuning fuzzy PI-PD controller with applying the Genetic Algorithm improved the performance of the system compared with the self-tuning fuzzy PI-PD controller without applying the Genetic Algorithm in terms of settling time, rise time, percentage overshoot and root mean square error. The percentage of improvement in terms of settling time and rise time is 33.5% and 47.6% respectively. The percentage overshoot of self-tuning fuzzy PI-PD controller from without applying Genetic Algorithm to with applying Genetic Algorithm is 15% to 10%. The percentage error of root mean square error is 12.46% where the root mean square error of self-tuning fuzzy PI-PD controller without applying Genetic Algorithm and with applying Genetic Algorithm is calculated and is reduced from 0.2806 to 0.2495. Therefore, the research had reached its objective which is the optimization of self-tuning fuzzy PI-PD controller using Genetic Algorithm can be performed with the help of Matlab software. The optimal gain value can be obtained by the help of Matlab software. The self-tuning fuzzy PI-PD controller can be tuned using systematic approach for better performance, since the controller is not explored to its fully capability.

Item Type: Final Year Project
Subjects: Technology > Mechanical engineering and machinery
Faculties: Faculty of Engineering and Technology > Bachelor of Engineering (Honours) Mechanical
Depositing User: Library Staff
Date Deposited: 10 Oct 2018 09:33
Last Modified: 10 Oct 2018 09:33
URI: https://eprints.tarc.edu.my/id/eprint/333