Abstract

Aiming at the problems of model uncertainty, external interference of road conditions, and inherent nonlinearity of lateral movement of autonomous driving vehicles, this paper proposes an effective control technology for an automatic steering system, namely, the receding horizon $H_{\infty }$ control, which has good path tracking performance and can overcome external interference. First, a two-degree-of-freedom vehicle model and a road model are established. Then, the Hamilton equation is established using Pontriagin’s minimum principle, and the optimal control solution and the most serious disturbance are solved based on the minimax principle. Finally, in order to evaluate the receding horizon $H_{\infty }$ autonomous steering control method, lane change simulation and hardware in the loop simulation are developed to describe the effect of receding horizon $H_{\mathrm {\infty }}$ . The simulation results show that the model predictive control (MPC) and linear matrix inequality (LMI) controller will exhibit oscillation and instability under the condition of external interference. To improve the stability, the $H_{\infty }$ controller reduces part of the performance, while the rolling horizon $H_{\mathrm {\infty }}$ strategy can ensure the robustness of automatic steering and has a certain anti-interference performance.

Highlights

  • Sensing and automotive electronic technologies have achieved significant development, and the commercialization of several advanced driving assist systems has been gradually realized over the last two decades

  • Owing to the external disturbances and nonlinearity of the steering system and vehicle dynamics, research on vehicle autonomous steering control for emergency obstacle avoidance in extreme driving situations still does not meet the requirements of commercialization [2]

  • Vehicle dynamics are subjected to severe external disturbances, which cause huge difficulties for autonomous steering control path tracking and cause a conflict between the controller’s robustness and performance[9]

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Summary

INTRODUCTION

Sensing and automotive electronic technologies have achieved significant development, and the commercialization of several advanced driving assist systems has been gradually realized over the last two decades. Vehicle dynamics are subjected to severe external disturbances, which cause huge difficulties for autonomous steering control path tracking and cause a conflict between the controller’s robustness and performance[9]. To solve the conflicts between path tracking performance and robustness in complex environments and extreme working conditions, inspired by the literature [24, 25], a receding horizon H∞ model predictive control framework based minimax criteria is proposed for vehicle trajectory tracking in this study. The three innovations of this paper are: 1) A new model predictive control method for vehicle trajectory tracking is proposed, which is based on a robust principle to realize road tracking technology that can solve the problem that the linearized prediction correction mechanism cannot essentially apply the traditional predictive control technology to the model uncertainty control of autonomous vehicles.

Vehicle model
Results and Analysis
Conclusions

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