Takagi-Sugeno Fuzzy-Based Robust H∞ Integrated Lane-Keeping and Direct Yaw Moment Controller of Unmanned Electric Vehicles

This article presents a Takagi-Sugeno (T-S) fuzzy-based robust H infinity integrated lane-keeping (LKS) and direct yaw moment control (DYC) system to improve the automatic driving performance of unmanned electric vehicles. First, a T-S fuzzy lateral model of unmanned electric vehicles is constructed, in which the cornering stiffness uncertainties, external disturbance, time varying look-ahead distance, and longitudinal velocity are considered. Second, an integrated LKS and DYC control system of unmanned electric vehicles is constructed to handle the time-varying features, parametric uncertainties, and overactuated actuators of unmanned electric vehicles, in which a T-S fuzzy-based robust H infinity output feedback control law is designed to produce the desired front wheel steering angle and external yaw moment, and a dynamic quadratic programming distribution law is presented to allocate the desired external yaw moment of unmanned electric vehicles. Finally, the simulation and experimental results are implemented to verify the availability of the proposed control scheme.

Automated summary

This study proposes a Takagi-Sugeno (T-S) fuzzy-based robust H infinity integrated lane-keeping (LKS) and direct yaw moment control (DYC) system to enhance the automatic driving performance of unmanned electric vehicles. The system considers the time-varying features and parametric uncertainties of the vehicles, and the effectiveness of the control scheme is verified through simulations and experiments.