Normal view MARC view ISBD view

Optimization of pid parameters for hydraulic positioning system utilizing variable weight grey-taguchi and particle swarm optimization / Nur Iffah Mohamed Azmi

By:

Nur Iffah Mohamed Azmi

Material type: Text

TextPublication details: Kuantan, Pahang : UMP, 2015Description: xviii, 121 p. : ill. ; 30 cm. + 1 CD-ROMISBN:

THE0005243(Local)

Subject(s):

Dissertation note: Thesis (Master of Engineering (Manufacturing)) -- Universiti Malaysia Pahang – 2015 Abstract: 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 proposedPSO-PID with the Variable Weight Grey-Taguchi DOE and the classical ZieglerNichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight GreyTaguchi 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-PIDparameter by applying the PSO-PID algorithm together with the Variable Weight GreyTaguchi DOE method as a good tuning method in the hydraulic positioning system.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings ( 2 )
Title notes ( 4 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Thesis	UMPLIB PEKAN	FKM .I34 2015 r Thesis (Browse shelf(Opens below))	1	Not for loan		0000107850
Thesis	UMPLIB PEKAN	CD 9685 \| FKM .I34 2015 r Thesis (Browse shelf(Opens below))	1	Not for loan		0000107851

Faculty of Manufacturing Engineering

Thesis (Master of Engineering (Manufacturing)) -- Universiti Malaysia Pahang – 2015

Bibliography : p. 107-113

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 proposedPSO-PID with the Variable Weight Grey-Taguchi DOE and the classical ZieglerNichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight GreyTaguchi 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-PIDparameter by applying the PSO-PID algorithm together with the Variable Weight GreyTaguchi DOE method as a good tuning method in the hydraulic positioning system.