Research on Fuzzy Logic Adaptive Sliding Mode Control for Autonomous Vehicles Considering Road Roll Angle

Trajectory tracking control for autonomous vehicles (AVs) has achieved satisfactory accuracy in most conditions. However, under the steering condition where the road has a roll angle, the tracking accuracy of the traditional controller decreases seriously, and the shaking of the output control quantity become stronger. To address this issue, this paper proposes a fuzzy logic adaptive sliding mode controller considering the road roll angle (FL-A-SMC-CRRA). Firstly, a three-degree-of-freedom (3DOF) vehicle model and a brush tire model are established with the road roll angle taken into consideration. Secondly, the controller is designed based on fuzzy logic and sliding mode control. Finally, three steering conditions with different road adhesion coefficients and road roll angles are simulated. The simulation results show that, in steering condition where the road have a roll angle, the tracking error of FL-A-SMC-CRRA is reduced by 65.98% compared with the traditional sliding mode controller (T-SMC), and the shaking of the sliding mode is suppressed by 68.49%. These advantages of FL-A-SMC-CRRA become more obvious when road conditions deteriorate.