Robust Fault Tolerant Path Tracking Control for Intelligent Vehicle under Steering System Faults

Malfunctions in the steering system inevitably result in a decline in lateral motion capacity, leading to unexpected conflicts between maintaining tracking reference path performance and satisfying current steering capacity. To resolve this conflict, we propose a supervisory-based fault-tolerant tracking control approach in this study. Our robust supervisory-based fault-tolerant control strategy comprises two main components. Firstly, a dynamically feasible motion interval predictor determines the lateral motion feasible set under uncertainties. Subsequently, new reference trajectories are reconstructed to accommodate current input constraints dynamically. These components operate as a unified supervisor to assess the reasonability of the reference path.Furthermore, a transformation function converts complex path-following goals into the desired yaw angle tracking objective. To ensure the robustness of our fault-tolerant controller, we employ a linear matrix inequality (LMI) based methodology to address tracking problems involving parametric uncertainties and input constraints. Finally, the effectiveness of our approach in addressing steering system faults with capacity degradation and uncertainties is demonstrated through extensive simulation results. Comparative analysis with stabilization-based fault-tolerant controllers reveals that our method significantly enhances vehicle stability and tracking performance under steering capacity degradation conditions.