The Effects of Weightage Values with Two Objective Functions in iPSO for Electro-Hydraulic Actuator System

Authors

  • Chai Mau Shern Centre for Robotics and Industrial Automation, Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Rozaimi Ghazali Centre for Robotics and Industrial Automation, Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Chong Shin Horng Centre for Robotics and Industrial Automation, Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Chong Chee Soon Centre for Robotics and Industrial Automation, Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia
  • Muhamad Fadli Ghani Malaysian Institute of Marine Engineering Technology (MIMET), Universiti Kuala Lumpur, Lumut, Perak, Malaysia
  • Yahaya Md Sam Control & Mechatronics Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor Bahru, Malaysia
  • Zulfatman Has Electrical Engineering Department, University of Muhammadiyah Malang, 65144 Malang, Indonesia

Keywords:

Electro-hydraulic Actuator System, Improved Particle Swarm Optimization, Linear Weight Summation

Abstract

In this paper, the Proportional-Integral-Derivative (PID) controller with improved Particle Swarm Optimization (iPSO) algorithm is proposed for the positioning control of nonlinear Electro-Hydraulic Actuator (EHA) system. PID controller is chosen to control the EHA system due to its popularity in industrial applications. The PID controller parameters will be tuned by using the iPSO algorithm to get the lowest overshoot percentage and steady-state error. The conventional PSO algorithm has only one objective function to get the optimum parameters. However, this is not enough to increase the control performance of the EHA system. Therefore, an improved Particle Swarm Optimization (iPSO) that includes the mean error and overshoot percentage as the two objective functions is proposed in this paper. The most popular method in PSO that included two objective functions is Linear Weight Summation (LWS). In this method, the two objective functions are combined with certain weightage into one equation to give the best control performance. This paper focuses on determining the suitable weightage between these two objective functions so that the EHA system can produce the best control performance with less overshoot and less error. Overshoot percentage and steady-state error are used to indicate the best control performance. The results showed that EHA system can perform better by using suitable weightage between the mean error and overshoot percentage.

Published

2021-07-13
فروشگاه اینترنتی