Improving PID controller of motor shaft angular position by using genetic algorithm

This study represents Genetic Algorithm optimization of PID parameters gain in model reference robust control system structure for desired position of incremental servomotor. Experiments had been took out via Lab-Volt 8063 Digital Servo system equipment at Servo Control Laboratory. The key issue for...

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Main Author:	Muhamad, Arif Abidin
Format:	Thesis
Language:	English English English
Published:	2015
Subjects:	TJ212-225 Control engineering systems Automatic machinery (General)
Online Access:	http://eprints.uthm.edu.my/1302/2/ARIF%20ABIDIN%20MUHAMAD%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/1302/1/24p%20ARIF%20ABIDIN%20MUHAMAD.pdf http://eprints.uthm.edu.my/1302/3/ARIF%20ABIDIN%20MUHAMAD%20WATERMARK.pdf
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spelling	my-uthm-ep.13022021-10-03T06:15:46Z Improving PID controller of motor shaft angular position by using genetic algorithm 2015-06 Muhamad, Arif Abidin TJ212-225 Control engineering systems. Automatic machinery (General) This study represents Genetic Algorithm optimization of PID parameters gain in model reference robust control system structure for desired position of incremental servomotor. Experiments had been took out via Lab-Volt 8063 Digital Servo system equipment at Servo Control Laboratory. The key issue for PID controllers is the accurate and efficient tuning of parameters. The plant repeatedly has a problem in achieving the desire position control and system performance have an oscillatory response and gives a slightly steady state error. This problem among other is affected by existing the nonlinearities component in the system, the system communication noise, and not optimize PID parameter. The existing PID controller tuning with the help of the offline Genetic Algorithms approach comprises of automatically obtaining the best possible outcome for the three parameters gain (Kp, Ki, Kd) for improving the steady state characteristics and performance indices. Their step responses are then compared with a tuned conventional Ziegler-Nichols based PID controller. This paper explores the well established methodologies of the literature to realize the workability and applicability of Genetic Algorithms for process control applications. At last, a comparative study done between ZN-PID experiment and GA-PID experiment shows that the GA optimal controller is highly effective and outperforms the PID controller in achieving an enhancing the output transient response with improvement percentage of rise time is 91.83%, settling time is 89.36% and maximum overshoot is 82.24%. The robust and automatic gains parameter calculator; GA based PID technique also proven to be time savers as they are much faster to be conducted than ZN method which is basically based on trial-and-error in getting the best PID values before the system can be narrowed down in getting the closest to the optimized value. 2015-06 Thesis http://eprints.uthm.edu.my/1302/ http://eprints.uthm.edu.my/1302/2/ARIF%20ABIDIN%20MUHAMAD%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/1302/1/24p%20ARIF%20ABIDIN%20MUHAMAD.pdf text en public http://eprints.uthm.edu.my/1302/3/ARIF%20ABIDIN%20MUHAMAD%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Faculty of Electrical and Electronic Engineering
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	TJ212-225 Control engineering systems Automatic machinery (General)
spellingShingle	TJ212-225 Control engineering systems Automatic machinery (General) Muhamad, Arif Abidin Improving PID controller of motor shaft angular position by using genetic algorithm
description	This study represents Genetic Algorithm optimization of PID parameters gain in model reference robust control system structure for desired position of incremental servomotor. Experiments had been took out via Lab-Volt 8063 Digital Servo system equipment at Servo Control Laboratory. The key issue for PID controllers is the accurate and efficient tuning of parameters. The plant repeatedly has a problem in achieving the desire position control and system performance have an oscillatory response and gives a slightly steady state error. This problem among other is affected by existing the nonlinearities component in the system, the system communication noise, and not optimize PID parameter. The existing PID controller tuning with the help of the offline Genetic Algorithms approach comprises of automatically obtaining the best possible outcome for the three parameters gain (Kp, Ki, Kd) for improving the steady state characteristics and performance indices. Their step responses are then compared with a tuned conventional Ziegler-Nichols based PID controller. This paper explores the well established methodologies of the literature to realize the workability and applicability of Genetic Algorithms for process control applications. At last, a comparative study done between ZN-PID experiment and GA-PID experiment shows that the GA optimal controller is highly effective and outperforms the PID controller in achieving an enhancing the output transient response with improvement percentage of rise time is 91.83%, settling time is 89.36% and maximum overshoot is 82.24%. The robust and automatic gains parameter calculator; GA based PID technique also proven to be time savers as they are much faster to be conducted than ZN method which is basically based on trial-and-error in getting the best PID values before the system can be narrowed down in getting the closest to the optimized value.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Muhamad, Arif Abidin
author_facet	Muhamad, Arif Abidin
author_sort	Muhamad, Arif Abidin
title	Improving PID controller of motor shaft angular position by using genetic algorithm
title_short	Improving PID controller of motor shaft angular position by using genetic algorithm
title_full	Improving PID controller of motor shaft angular position by using genetic algorithm
title_fullStr	Improving PID controller of motor shaft angular position by using genetic algorithm
title_full_unstemmed	Improving PID controller of motor shaft angular position by using genetic algorithm
title_sort	improving pid controller of motor shaft angular position by using genetic algorithm
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Faculty of Electrical and Electronic Engineering
publishDate	2015
url	http://eprints.uthm.edu.my/1302/2/ARIF%20ABIDIN%20MUHAMAD%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/1302/1/24p%20ARIF%20ABIDIN%20MUHAMAD.pdf http://eprints.uthm.edu.my/1302/3/ARIF%20ABIDIN%20MUHAMAD%20WATERMARK.pdf
_version_	1747830765815595008

Improving PID controller of motor shaft angular position by using genetic algorithm

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