Intelligent robust control of active suspension system

Abstract

This project presents a modelling and control of an active suspension system with hydraulic actuator dynamic for a quarter car model. The objective of designing a controller for the car suspension system is to improve the ride comfort while maintaining the constraints on to the suspension travel and tire deformation subject to different road profile. In this research, a cascade control algorithm which consists of the inner loop controller for force tracking control of the hydraulic actuator model and the outer loop controller for disturbance rejection control is proposed. Particle swarm optimization (PSO) algorithm is employed to optimize the PI controller parameters for force tracking control of the hydraulic actuator model. The outer loop controller utilizes a sliding mode controller scheme which incorporates PSO algorithm to efficiently reduce the influence of mismatched disturbance during sliding motion. In addition to that, the performance of the proposed sliding mode controller is compared with the LQR controller and the existing passive suspension system. Similarly, the values of Q and R for the LQR controller are optimized by PSO algorithm. A simulation study is performed to show the effectiveness and robustness of the proposed control algorithm. Eventually the results prove that the proposed controller improves the ride comfort by maintaining the other constrains (the suspension travel, tire deflection, and control force) in their limits.