Vibration control of semi-active suspension system using PID controller with advanced firefly algorithm and particle swarm optimization

Magnetorheological (MR) damper control for semi-active system is one of the areas of interest investigated to improve the ride comfort and stability of vehicle performance. Many types of controllers used to control the semi-active MR damper have recently been investigated by previous researchers. It is found that the improper design of control scheme has led to an unpredictable optimum target force. Therefore, this study aims to investigate an intelligent optimizer called advanced firefly algorithm (AFA) to compute the proportional-integral-derivative (PID) controller for semi-active suspension system. The performance of the PID controller with the AFA tuning was investigated and compared to the original FA technique and other conventional and intelligent optimizers as well as non-PID controller namely as heuristic method, particle swarm optimization (PSO) and Skyhook controller. A MATLAB Simulation environment was used to generate the simulation model of semi-active suspension system complete will all control elements. The study of the controllers has shown a significant improvement as the proposed PID-AFA is capable of reducing the amplitude of the sprung acceleration and body acceleration responses up to 56.5% and 67.1%, respectively compared to PID-HEURISTIC, PID-FA, PID-PSO, Skyhook and passive systems.