A T-S Fuzzy Based Model Predictive Control Method for the Direct Yaw Moment Control System Design

Abstract Distributed drive electric vehicles (DDEVs) endow the ability to improve the vehicle stability performance through the direct yaw-moment control (DYC). However, the nonlinear characteristics pose a great challenge to the vehicle dynamics control. For this purpose, this paper studies the DYC through the Takagi-Sugeno (T-S) fuzzy based model predictive control to deal with the nonlinear challenge. First, a T-S fuzzy based vehicle dynamics model is established to describe the time-varying tire cornering stiffness and vehicle speeds and thus the uncertain parameters can be represented by the norm-bounded uncertainties. Then, a robust model predictive control (MPC) is developed to guarantee the vehicle handling stability. A feasible solution can be obtained through a set of linear matrix inequalities (LMIs). Finally, the tests are conducted by the Carsim/Simulink joint platform to verify the proposed method. The comparative results show that the proposed strategy can effectively guarantee the vehicle lateral stability while handling the nonlinear challenge.