Performance Evaluation of EHA System using Weight Aggregation Strategy in MOPSO-PID

Abstract

In this paper, an improved Particle Swarm Optimization (PSO) that combines the Proportional-Integral-Derivative (PID) controller for positioning control in Electro-Hydraulic Actuator (EHA) system is proposed. Conventionally, PSO with single objective function is designed to determine the optimal parameters of the controller. However, PSO with single objective function might not solve the problem effectively. Hence, a Multi-Objective PSO (MOPSO) is proposed in this work. Two objective functions will be used in the optimization task, which includes mean error and overshoot percentage. The most popular method in MOPSO is Linear Weight Summation (LWS). This paper focuses on investigating the effect of different weight factors combination between mean error and overshoot. Time domain analysis such as overshoot percentage, steady-state error, and mean error will be used to analyse the positioning performance of the EHA system. The results showed that the EHA system performed better by using the best combination of weight factors between mean error and overshoot.