State-Feedback Path Tracking Control for Autonomous Vehicle with Sampled-Data Measurements

This paper investigates the problem of fuzzy H
_∞
control for path tracking in autonomous vehicle with sampled-data measurements. Considering the variations of vehicle mass and velocity, a Takagi-Sugeno fuzzy model is proposed to describe the lateral vehicle dynamics. Under Lyapunov stability framework, sufficient conditions in terms of linear matrix inequalities have been derived for the stability of the path tracking system and the existence of admissible state feedback controllers, is also given for the closed-loop system to be asymptotically stable with a prescribed H
_∞
disturbance attenuation level. Finally, the joint simulation (Matlab/Simulink and Carsim) results are provided to illustrate the effectiveness of the proposed method.