Electronic Differential Control System Based on Particle Swarm Optimization and PID Control

Abstract

For the front wheel steering, the control effect of the four-wheel hub-driven electric vehicle driven by the rear wheel is not accurate and stable. It is proposed to replace the traditional PID control system with the particle swarm algorithm to realize the online optimization of the PID regulator parameters. The simulation model of the improved system is built in MATLAB. Compared with the conventional PID control method, the results show that the improved four-wheel drive system has a smaller slip ratio between the left rear wheel and the right rear wheel, which improves the directional stability and braking efficiency of the wheel electric vehicle.

Optimization of PID control parameters for marine dual-fuel engine using improved particle swarm algorithm

“…The second direction revolves around augmenting the diversity of the population. By integrating genetic algorithms and introducing velocity mutation, position mutation, and other techniques, the diversity of particles can be increased, thereby enhancing global search capability 44 . These proposed solutions effectively address the challenges associated with global search difficulty.…”