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Wavelets based Recurrent Adaptive NeuroFuzzy approach for active full car suspension control

The main objective of this paper is to design an efficient active suspension control system for the full car model. The conventional passive suspension and semi-active suspension systems do not provide good vehicle's handling against the road disturbances and ride comfort. To tackle this problem, Wavelets based Recurrent Adaptive NeuroFuzzy (WRANF) control approach is used for active suspension control. The WRANF control is flexible, has robustness abilities and good generalization properties against the dynamic systems. The performance of the active suspension system is determined by the displacement and acceleration of heave, pitch, roll and seat of the vehicle. To validate the effectiveness of the proposed control scheme, the full car model is simulated in MATLAB/Simulink and subjected to a varying road profile. The performance of the WRANF based active suspension system is compared with passive and semi-active suspension system.