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Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization

Nur Iffah, Mohamed Azmi and Kamal Arifin, Mat Piah and Wan Azhar, Wan Yusoff and F. R. M., Romlay (2017) Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization. In: The 4th Asia Pacific Conference on Manufacturing Systems and The 3rd International Manufacturing Engineering Conference (APCOMS-IMEC 2017), 7-8 December 2017 , Yogyakarta, Indonesia. pp. 1-6.. (Unpublished)

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Abstract

Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. 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 particle velocity limit 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. Furthermore, the physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning method 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 tuning method in the hydraulic positioning system.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: PID Parameters; Taguchi Method; Particle swarm optimization
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Manufacturing Engineering
Faculty of Mechanical Engineering
Depositing User: Noorul Farina Arifin
Date Deposited: 28 Dec 2017 06:50
Last Modified: 26 Sep 2018 08:08
URI: http://umpir.ump.edu.my/id/eprint/19722
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