The Fault Detection and Isolation Design for 4WS Vehicles Based on Directional Residuals Under External Disturbance

This paper presents an integrated fault detection and isolation (FDI) framework for actuator anomalies in fourwheel steering (4WS) systems. First, a lateral dynamics model for 4WS vehicles is developed by incorporating the Takagi-Sugeno fuzzy model, while accounting for external disturbances and sensor measurement noise. This improved model is designed to address unmodeled dynamics arising from variations in longitudinal velocity. Subsequently, a residual generation observer is developed by synthesizing <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$H_{-}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$L_{\infty}$</tex> performance indices, achieving an optimal balance between disturbance and fault sensitivity. To enable precise fault localization, directional residual vectors are systematically constructed, with actuator faults being identified through geometric correlation analysis between the fault feature vectors and the generated residual vectors. Finally, the effectiveness and feasibility of the proposed method in FDI are verified by simulation experiments.