Combined Path Following and Direct Yaw-Moment Control for Unmanned Electric Vehicles Based on Event-Triggered T–S Fuzzy Method.

This paper focuses on the combined path following (PF) and direct yaw-moment control (DYC) problem of unmanned electric vehicles (UEVs) based on an event-triggered Takagi–Sugeno (T–S) fuzzy method. First, to describe the parameter uncertainties and nonlinear tire dynamics of UEVs, a T–S fuzzy dynamic model is developed for performance analysis and controller design of the vehicle lateral dynamic system. Second, as the signal transmission inevitably suffers from delay and data dropouts because of the limited network bandwidth, an event-triggered scheme is constructed to complete the communication scheduling and save the communication resource. Third, considering that there is an unavoidable asynchronous constraint between the fuzzy system and the fuzzy controller due to the communication delay, a hierarchical event-triggered fuzzy controller design approach is given via a new Lyapunov functional. Moreover, a differential distribution scheme is introduced to obtain the desired torque of each tire of the vehicle. Finally, experimental results validate that the presented controller in this paper is able to improve the path following accuracy by 61.93% with a resource economization 92.04% compared with the existing method. [ABSTRACT FROM AUTHOR]