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This paper proposes a novel approach to designing a stochastic sliding mode controller for a suspension system. The controller takes into account the stochastic nature of uncertainties in the system, assuming that all random uncertainties are independent and have arbitrary intensity. The suspension system is modeled using Ito stochastic equations, considering both parametric stochastic perturbations and uncertainty of the road roughness. A nonlinear sliding surface is designed and a sliding mode controller is implemented for the proposed model, to ensure the stability of the stochastic system dynamics. This method guarantees asymptotic stability with probability one for all admissible mismatched uncertainties. Additionally, the synthesized sliding mode controller ensures the reachability of the specified sliding surface. Numerical simulations are conducted to validate the effectiveness of the proposed method. Also, it is compared with the deterministic sliding mode controller. The results demonstrate the efficiency of the designed stochastic sliding mode controller in providing better performance in terms of energy consumption and response rate of the suspension system.
Zahiripour et al. (Fri,) studied this question.