000			02986ntm a2200277 a 4500
001			vtls000093889
003			KUKTEM
005			20251117113321.0
008			160316t2015 my a f 000 0 eng d
020			_aTHE0005243(Local)
039		9	_a201905141514 _bhanafiah _y201603161557 _zhuda
040			_aUMP
090			_aFKM .I34 2015 r Thesis
100	0		_aNur Iffah Mohamed Azmi
245	1		_aOptimization of pid parameters for hydraulic positioning system utilizing variable weight grey-taguchi and particle swarm optimization / _cNur Iffah Mohamed Azmi
260			_aKuantan, Pahang : _bUMP, _c2015
300			_axviii, 121 p. : _bill. ; _c30 cm. + _e1 CD-ROM
500			_aFaculty of Manufacturing Engineering
502			_aThesis (Master of Engineering (Manufacturing)) -- Universiti Malaysia Pahang – 2015
504			_aBibliography : p. 107-113
520	3		_aController 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.
610	2	0	_aFaculty of Manufacturing Engineering _xDissertations
650		0	_aUniversities and Colleges _xDissertations
650		0	_aTheses
999			_aVIRTUA40 _c6636 _d6642
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