Sliding mode control (SMC) has gained a wide acceptance in recent years due to its simplicity and robustness. Discrete-time sliding mode control (DSMC) is advantageous over its continuous-time counterparts due to the development in digital signal processing. However, little attention has been paid to the application of DSMC to the design of active suspensions. In this research, DSMC-based active suspensions are designed using both the SMC theory and a genetic algorithm (GA) to improve the ride quality and handling performance with the full states observed by a discrete-time Kalman filter. The extensive computation demand levied by the GA is handled by using the parallel computation technique. The proposed optimization-based SMC approach simplifies the design process and improves the overall performance of the controlled system.

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