Robust handling enhancement on a slippery road using quantitative feedback theory

In the present paper, a quantitative feedback theory controller is developed to control the lateral motion and yawing motion of a car equipped with a mechatronic front-wheel steering system. The overall objective is to track the yaw rate with the aim of achieving satisfactory performance specifications for the lateral dynamics of the vehicle, regarding different road conditions as well as uncertain parameters such as the mass, the velocity and the moment of inertia of the vehicle. To establish an accurate model of the vehicle, a seven-degree-of-freedom model is considered. An observer for detecting the cornering stiffnesses of the tyres based on the beta-less method is designed. In spite of the estimation of the cornering stiffnesses, a wide range of uncertainties for this parameter in the design procedure of the quantitative feedback theory controller is predicted. The effects of practical data acquisition and processing time delays as well as the dynamic behaviours of the actuators are studied. The simulations show that the designed quantitative feedback theory controller has a significant effect on stable cornering in the presence of the numerous wide-ranging uncertainties. Nevertheless, for satisfactory behaviour of the controller, there are some important practical considerations such as the fast response of actuators and the short processing time of the computational electronic unit especially for a slippery road.