03189ntm a2200301 a 4500001001400000003000700014005001700021008004100038020002200079039006500101040000800166090003200174100002700206245016500233260003400398300006000432500004100492502008900533504003000622520172500652650003702377650002002414856005702434952013402491952014502625999002502770999009202795vtls000091346KUKTEM20251117113311.0150928t2015    my da  f abm  000 0 eng d  aTHE0006153(Local) 9a201905151610baidac201710120958daishahy201509281704zasma  aUMP  aTJ223.P55 134 2015 r Thesis0 aNur Iffah Mohamed Azmi1 aOptimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization /cNur Iffah Mohamed Azmi  aKuantan, Pahang :bUMP,c2015  axviii, 121 p. :bill. (some col.) ;c30 cm. +e1 CD ROM  aFaculty of Manufacturing Engineering  aThesis (Master of Engineering (Manufacturing)) -- Universiti Malaysia Pahang -- 2015  aBibliography : p. 107-1133 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 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. 0aProportional-Integral-Derivative 0aPID controllers40uhttp://ecollib.ump.edu.my/3776/zLibrary access only  00102lcc4071a20000b20000d2019-09-04l0oTJ223.P55 134 2015 r Thesisp0000100318r2019-09-04 00:00:00t1w2019-09-04yTHESIS  00102lcc407-2a20000b20000d2019-09-04l0oCD 8907 | TJ223.P55 134 2015 r Thesisp0000100319r2019-09-04 00:00:00t1w2019-09-04yTHESIS  aVIRTUA40c6344d6350  aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5000*5020*5040*5200*6500*6501*8560*9992