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Algorithms 2018, 11(12), 205; https://doi.org/10.3390/a11120205

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

School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130022, China
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Received: 19 October 2018 / Revised: 30 November 2018 / Accepted: 30 November 2018 / Published: 14 December 2018
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Abstract

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. View Full-Text
Keywords: active suspension system; optimal sliding mode control; genetic algorithm; switching function; weight coefficients active suspension system; optimal sliding mode control; genetic algorithm; switching function; weight coefficients
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Zhou, C.; Liu, X.; Chen, W.; Xu, F.; Cao, B. Optimal Sliding Mode Control for an Active Suspension System Based on a Genetic Algorithm. Algorithms 2018, 11, 205.

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