T-S Fuzzy Model Predictive Control for Vehicle Yaw Stability in Nonlinear Region

Safety at high speed is the most important performance of autonomous vehicle. Wherein, yaw stability control (YSC) is a key technology to improve vehicle safety. However, the high-speed vehicles are easy to be out of control in nonlinear region, which will result in serious accidents. This study proposes a model predictive control (MPC) method based on the Takagi-Sugeno (T-S) fuzzy model to realize YSC in the nonlinear region. Firstly, a T-S fuzzy model of vehicle is established based on a two-degree-of-freedom model to describe the vehicle dynamic characteristics in the nonlinear region. Then, a robust MPC is designed and its solution is given in the linear matrix inequalities (LMIs) form. Next, a sliding mode controller (SMC) is proposed to prevent wheel lock in the YSC process. Finally, the proposed strategy is verified in simulations and experiments. The results show that the proposed strategy has similar performance in vehicle stable region with linear MPC, and shows the ability to suppress the instability of the vehicle in the nonlinear region, and its computation burden is acceptable.

Automated summary

This study proposes a model predictive control (MPC) method based on the Takagi-Sugeno (T-S) fuzzy model to realize yaw stability control (YSC) in the nonlinear region. The results show that the proposed strategy has similar performance in the vehicle stable region with linear MPC, and it is able to suppress the instability of the vehicle in the nonlinear region, with an acceptable computation burden.