Fuzzy steering control for autonomous vehicles under actuator saturation: Design and experiments

Abstract

This paper presents a new control method for autonomous vehicles. The design goal is to perform the automatic lane keeping under multiple system constraints, namely actuator saturation of the steering system, roads with unknown curvature and uncertain lateral wind force. Such system constraints are explicitly taken into account in the control design procedure. To achieve this goal, we propose a new constrained Takagi–Sugeno fuzzy model-based control method using fuzzy Lyapunov control framework. The resulting non-parallel distributed compensation controller is able to handle not only various system constraints but also a large variation range of vehicle speed. In particular, Taylor’s approximation method is exploited to reduce not only the numerical complexity for real-time implementation but also the conservatism of the results. The design conditions are strictly expressed in terms of linear matrix inequalities which can be efficiently solved with available numerical solvers. The effectiveness of the proposed control method is demonstrated through both simulation and hardware experiments with various driving scenarios.