Optimal Sliding Mode Control for an Active Suspension System Based on a Genetic Algorithm

• Main Authors: Chen Zhou, Xinhui Liu, Wei Chen, Feixiang Xu, Bingwei Cao
• Format: Article
• Language: English
• Published: MDPI AG 2018-12-01
• Series: Algorithms
• Subjects: active suspension system; optimal sliding mode control; genetic algorithm; switching function; weight coefficients
• Online Access: https://www.mdpi.com/1999-4893/11/12/205

In order to improve the dynamic quality of traditional sliding mode control for an active suspension system, an optimal sliding mode control (OSMC) based on a genetic algorithm (GA) is proposed. First, the overall structure and control principle of the active suspension system are introduced. Second, the mathematical model of the quarter car active suspension system is established. Third, a sliding mode control (SMC) controller is designed to manipulate the active force to control the active suspension system. Fourth, GA is applied to optimize the weight coefficients of an SMC switching function and the parameters of the control law. Finally, the simulation model is built based on MATLAB/Simulink (version 2014a), and the simulations are performed and analyzed with the proposed control strategy to identify its performance. The simulation results show that the OSMC controller tuned using a GA has better control performance than the traditional SMC controller.