Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization

Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Especially on hydraulic positioning system that is highly nonlinear and difficult to be controlled whereby PID parameters needs to be tuned to obtain optimum performance criteria. Tu...

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Main Author:	Nur Iffah, Mohamed Azmi
Format:	Thesis
Language:	English
Published:	2014
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/11514/19/Optimization%20of%20PID%20parameters%20for%20hydraulic%20positioning%20system%20utilizing%20variable%20weight%20Grey-Taguchi%20and%20particle%20swarm%20optimization.pdf
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id	my-ump-ir.11514
record_format	uketd_dc
spelling	my-ump-ir.115142021-11-02T06:16:02Z Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization 2014 Nur Iffah, Mohamed Azmi TJ Mechanical engineering and machinery Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Especially on hydraulic positioning system that is highly nonlinear and difficult to be controlled whereby PID parameters needs to be tuned to obtain optimum performance criteria. Tuning PID control method is divided into two namely the classical methods and the methods of artificial intelligence. Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. This is done by conducting the DOE on the two PSO optimizing parameters: the limit of change in particle velocity and the weight distribution factor. Computer simulations and physical experiments were conducted by using the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE and the classical Ziegler-Nichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE has reduced the rise time by 48.13% and settling time by 48.57% compared to the Ziegler-Nichols method. Physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning responds better than Ziegler-Nichols tuning. In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a good tuning method in the hydraulic positioning system. 2014 Thesis http://umpir.ump.edu.my/id/eprint/11514/ http://umpir.ump.edu.my/id/eprint/11514/19/Optimization%20of%20PID%20parameters%20for%20hydraulic%20positioning%20system%20utilizing%20variable%20weight%20Grey-Taguchi%20and%20particle%20swarm%20optimization.pdf pdf en public masters Universiti Malaysia Pahang Faculty of Manufacturing Engineering
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
collection	UMPSA Institutional Repository
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Nur Iffah, Mohamed Azmi Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
description	Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Especially on hydraulic positioning system that is highly nonlinear and difficult to be controlled whereby PID parameters needs to be tuned to obtain optimum performance criteria. Tuning PID control method is divided into two namely the classical methods and the methods of artificial intelligence. Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. This is done by conducting the DOE on the two PSO optimizing parameters: the limit of change in particle velocity and the weight distribution factor. Computer simulations and physical experiments were conducted by using the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE and the classical Ziegler-Nichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE has reduced the rise time by 48.13% and settling time by 48.57% compared to the Ziegler-Nichols method. Physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning responds better than Ziegler-Nichols tuning. In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a good tuning method in the hydraulic positioning system.
format	Thesis
qualification_level	Master's degree
author	Nur Iffah, Mohamed Azmi
author_facet	Nur Iffah, Mohamed Azmi
author_sort	Nur Iffah, Mohamed Azmi
title	Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
title_short	Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
title_full	Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
title_fullStr	Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
title_full_unstemmed	Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
title_sort	optimization of pid parameters for hydraulic positioning system utilizing variable weight grey-taguchi and particle swarm optimization
granting_institution	Universiti Malaysia Pahang
granting_department	Faculty of Manufacturing Engineering
publishDate	2014
url	http://umpir.ump.edu.my/id/eprint/11514/19/Optimization%20of%20PID%20parameters%20for%20hydraulic%20positioning%20system%20utilizing%20variable%20weight%20Grey-Taguchi%20and%20particle%20swarm%20optimization.pdf
_version_	1783731942628261888

Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization

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