期刊名称：International Journal of Advances in Soft Computing and Its Applications
印刷版ISSN：2074-8523
出版年度：2014
卷号：6
期号：3
出版社：International Center for Scientific Research and Studies
摘要：This paper proposes a cascade control algorithm of an active suspension system (ASS) 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, which is subjected to different road profiles. The control algorithm is based on the fusion of robust control and computational intelligence techniques 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. Particle swarm optimization (PSO) algorithm is employed to optimize the Proportional-integral (PI) controller parameters for force tracking control of the hydraulic actuator model. Similarly, the PSO algorithm is utilized in the outer loop controller to search for the optimal values of the weighting matrices for the linear quadratic optimal control (LQR) such that the desired performance of the ASS is guaranteed. In comparison with the passive suspension system, the simulation results demonstrate the superiority of proposed PSO-based controller, where it significantly improved the ride comfort by maintaining the other constraints (the suspension travel, tire deflection, and control force) in their limits
关键词：Active Suspension System; linear quadratic regulator; Proportional ; Integral Control; Particle Swarm Optimization
