Active Front Wheel Steering System using Yaw Rate Estimation based Fuzzy Logic Due to Various Lateral Wind Disturbance

Abstract

The paper devised and compared the performances of PID, fuzzy-tuned PID and fuzzy logic controller in an Active Front Wheel Steering system to stabilize a 9-DOF nonlinear passenger vehicle when subjected to lateral wind disturbance. The vehicle model was derived mathematically and verified with data from IPG CarMaker at a longitudinal speed of 80 km/h. Initially, the disturbance test was conducted using three lateral wind disturbance profiles to test for controller resiliency with zero steering input. Then, a simple but effective yaw rate observer was derived without compromising the linearity of the vehicle model to simulate the disturbance test with a double lane change (DLC) steering input. A more extreme disturbance magnitude was evaluated in the latter test using the developed control designs. The three controllers showed good performances in both disturbance tests, with fuzzy logic having the lowest error out of the three, which is less than 5% for using the estimated yaw rate observer.