A Reliable Robust Control Method for Vehicle Lateral Dynamics With Preview Driver Model

To address the vehicle lateral dynamics control in practical application with nonlinearity, uncertainty, detection faults and disturbances, this paper describes three key elements in the controller design that address the safety and comfort performance challenges, i.e., high precision modeling, redundant detection and robust control. Firstly, the vehicle dynamics model, tire model and preview driver model are augmented into a coupled lateral dynamics model, which is linearized and then transformed into a linear parameter varying (LPV) model with the varying motion states and tire cornering stiffness. Secondly, a redundant detection strategy is proposed for the lane-marker-based lateral control system to improve the reliability. According to the different detection states and sequences, an $H_{\infty } $ state observer is designed for the vehicle motion state estimation, where a tracking and prediction strategy of the lane markers is considered for the constraint of the dwell time to guarantee the exponential stability. Considering the linearization errors, model uncertainty and disturbances in the LPV model, the $H_{\infty } $ observer-based controller is designed to improve the stability and robustness based on the Lyapunov stability theory. Lastly, three similar experiment scenarios are given to demonstrate the effectiveness of the proposed method.