Improved Performance of Active Suspension System Using COA Optimized FLC for Full Car With Driver Model

Abstract

Suspension in a vehicle is provided primarily to improve the passenger comfort and vehicle handling for the automobiles moving under any road conditions. Because of the non-linear characteristics of the vehicle, fuzzy logic controller (FLC) fed active suspension system is proposed for a full car with driver vehicle model. This controller dynamics are optimized by meta-heuristic optimization algorithm namely big bang–big crunch (BBBC) optimization and coyote optimization algorithm (COA). The passive system dynamics are compared with controller fed and optimized controller fed system under bump and random road inputs. The passive and active model is simulated in MATLAB/Simulink environment. The results are compared based upon root mean square values of head acceleration, body acceleration, pitch acceleration, roll acceleration, and power spectrum density of head acceleration. The results indicate that implementation of COA optimized FLC is effective in improving ride quality and road handling of the vehicle.