Adaptive Neuro-fuzzy Sliding Mode Control Based Strategy for Active Suspension Control

Abstract

Suspension system of a vehicle is used to minimize the effect of different road disturbances on ride comfort and to improve the vehicle control. A passive suspension system responds only to the deflection of the strut. While, the semi active system setup can dissipate energy from the system at an appropriate time, in a way or amount that is right for all the variables in the system. The main objective of this work is to design an efficient active suspension control for full car model with 8-Degrees of Freedom (DOF) using adaptive soft computing technique. So, in this study, an Adaptive Neuro-Fuzzy based Sliding Mode Control (ANFSMC) is used for full car active suspension system to improve the ride comfort and vehicle stability. ANFSMC is adapted in such a way as to estimate online the unknown dynamics and provide feedback response. The detailed mathematical model of ANFSMC has been developed and successfully applied to a full car model. The robustness of the presented ANFSMC has been proved on the basis of different performance indices. The analysis of MATLAB/SMULINK based simulation results reveals that the proposed ANFSMC has better ride comfort and vehicle handling as compared to passive or semi-active suspension systems.