APPLICATION OF MODEL-BASED PREDICTIVE AND ROBUST LOOP SHAPING CONTROL TO AUTOMATIC CAR STEERING

Abstract The automatic steering assistance system presented in this paper takes advantage of the technique of Model-based predictive control (MPC) of systems with hard input constraints in order to compute the appropriate steering angle of the front tires. In addition the Quantitative Feedback Theory (QFT) is used to find a robust controller that maintains the key properties of the loop for the implementation of the Model-based Predictive Controller input, despite uncertainty, i.e. stability, tracking performance and disturbance rejection. The procedure involves deriving a steering angle rate from the front tire angle and applying it to the steering column. The feasibility of the proposed assistance system is evaluated in a simulation using Matlab/Simulink and a test vehicle. The results demonstrate the effectiveness of the automatic steering system in lane keeping and yaw dynamic improvement.