Vehicle lateral motion control via robust delay-dependent Takagi-Sugeno strategy

Abstract

Presented in this research paper is an integrated direct yaw moment control (DYC) and active front steering (AFS) for an uncertain vehicle lateral dynamics model considering network-induced communication delay, which is a time-varying continuous function with a known upper bound. Firstly, we consider tire cornering stiffness as a non-linear norm-bounded uncertain system that is modeled by fuzzy membership functions, and then vehicle lateral dynamics model is expressed by a set of linear Takagi-Sugeno (T-S) uncertain fuzzy models. Secondly, since the network-induced communication delay in vehicle control system is an inherent reason for stability and performance degradation, we derive a robust delay-dependent [Formula: see text] control methodology via the Lyapunov-Krasovskii functional for stability and performance conditions of the closed-loop system. For the synthesis, the robust control method is employed within the T-S fuzzy-model-based analysis framework and formulations are performed based on the solution of delay-dependent linear matrix inequalities (LMIs). The simulation study is presented using MATLAB/Simulink to show the achieved improvements in tracking variables via the designed robust fuzzy [Formula: see text] state-feedback controller. The proposed fuzzy robust delay-dependent controller is compared with a linear robust delay-dependent controller to clearly show the tracking improvements for different road conditions. Moreover, a performance-based analysis is carried out to demonstrate the advantage of the design with respect to different delay values. It is confirmed from the analysis results that the proposed fuzzy controller can successfully stabilize and possess improved tracking performance for vehicle lateral motion control.