Sliding mode control design for active suspension systems using quantum particle swarm optimisation

In this paper, the problem of sliding mode control design for nonlinear 1/4 active suspension under road excitation most in line with the real situation is investigated. By using the theory of differential geometry, the suspension model is linearised. The sliding mode controller based on exponential approach law is adopted. And the quantum particle swarm optimisation (QPSO) algorithm is used to optimise the switching function C. The ratio of the root mean square (RMS) value of the performance index is used to construct the fitness value to improve the dynamic performance of the system. Three white noise pavement design methods are compared to select the road excitation. The simulation results show that suspension with sliding mode controller based on QPSO outperforms the ordinary sliding mode control suspension and fuzzy control suspension. The results also prove the importance of sliding surface parameter selection and the superiority and effectiveness of this control method.