Enhancing Electro-Hydraulic Load Simulator Performance Through Variable Arm Length and Particle Swarm-Optimized Controllers

Abstract

This study presents a novel approach to improve the loading characteristics of an electro-hydraulic load simulator by introducing a variable arm length mechanism and employing advanced control strategies rooted in Particle Swarm Optimization (PSO). The design enhancements focus on optimizing the physical connection between the steering gear system and the load system, resulting in an electro-hydraulic load simulator equipped with adjustable arm length. Through a meticulous analysis of the ideal pivot position for the rocker lever, a fuzzy Proportional-Integral-Derivative (PID) controller based on PSO has been developed for the steering gear system. In recognition of the PSO algorithm’s susceptibility to local optima convergence, a fuzzy PID controller employing Single-Particle Random Search (SSPSO) has also been devised for the load system. To assess the effectiveness of this innovative hardware configuration and controller implementation in mitigating over-suppression, comprehensive joint simulation experiments were conducted. The results unequivocally indicate that the incorporation of the variable arm length structure, along with the PSO-based fuzzy PID controller optimized using binding factors, substantially enhances the dynamic loading performance of the electro-hydraulic load simulator. This enhancement translates into superior loading accuracy and overall performance metrics, establishing this research as a valuable reference for future investigations in this field.