Model Predictive Control of Half-Car Active Suspension Systems Using Particle Swarm Optimisation
Jimoh O. Pedro, Sakhile M.S. Nhlapo, Lindokuhle J. Mpanza
Abstract
This paper presents the design of a particle swarm-optimised model predictive controller (MPC) for a half-car nonlinear electrohydraulic suspension system as it traverses a deterministic road disturbance. The particle swarm optimisation (PSO) algorithm uses an objective function which is based on conflicting active vehicle suspension system (AVSS) design specifications such as: ride comfort, road holding, road handling, suspension travel and power consumption. An inner-loop PID-based force feedback control is incorporated in the design to ensure good force tracking. The half-car model is composed of nonlinear suspensions and actuator dynamics. Simulation results demonstrate the superior performance of the proposed control scheme over the passive vehicle suspension system (PVSS) and the non-optimised MPC in rejecting the deterministic road disturbance.