Event-triggered Adaptive Robust Control for Lateral Stability of Steer-by-wire Vehicles with Abrupt Nonlinear Faults
2022-01-1112
03/29/2022
- Event
- Content
- Owing to the fact that autonomous vehicles equipped with active front steering (AFS) have the features of time-varying, uncertainties, high rate of fault and high burden on the in-vehicle networks, this article studies the adaptive robust control problem for improving steer-by-wire (SBW) vehicles lateral stability in the presence of abrupt nonlinear faults. Firstly, a robust H∞ controller, as an upper-level controller, is designed to obtain the corrected steering angle for driving both the yaw rate and the sideslip angle to achieve their desired values. Takagi-Sugeno (T-S) fuzzy modeling approach which has shown the extraordinary ability in coping with the issue of nonlinear is applied to deal with the challenge of the changing longitudinal velocity. The output of upper controller can be calculated by parallel-distribute-compensation (PDC) scheme. Then, an event triggered adaptive fault tolerant lower controller is proposed to track the desired front wheel steering angle offered by the upper controller with fewer communication resources and strong robustness. By employing a backstepping technique, the tracking performance is improved. The dynamic surface control (DSC) technique is used to avoid the problem of repeated differentiations and Nussbaum function is adopted to overcome the problem of unknown control gain and control direction. Both of the stability of upper and lower controllers can be guarantee by Lyapunov functions. Finally, the simulations of Matlab/Simulink are given to show that the proposed control strategy can effectively deal with the abrupt nonlinear fault via less communication resources and perform better in ensuring the yaw stability of the vehicle.
- Citation
- zheng, g., Xie, Z., and Zhao, J., "Event-triggered Adaptive Robust Control for Lateral Stability of Steer-by-wire Vehicles with Abrupt Nonlinear Faults," SAE Technical Paper 2022-01-1112, 2022, .