Trajectory Tracking of Autonomous Ground Vehicles with Actuator Dead Zones

Pengfei Zhang,Qiyuan Chen,Tingting Yang,Yiyu Cai

doi:10.1155/2021/2914190

Pengfei Zhang, Qiyuan Chen + Show 2 more

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https://doi.org/10.1155/2021/2914190

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Abstract

This paper investigates the trajectory tracking problem of autonomous ground vehicles (AGVs). The dynamics considered feature external disturbances, model uncertainties, and actuator dead zones. First, a novel time-varying yaw guidance law is proposed based on the line of sight method. By a state transformation, the AGV is proved to realize trajectory tracking control under the premise of eliminating guidance deviation. Second, a fixed time dead zone compensation control method is introduced to ensure the yaw angle tracking of the presented guidance. Furthermore, an improved fixed-time disturbance observer is proposed to compensate for the influence of the actuator dead zone on disturbance observation. Finally, the trajectory tracking control strategy is designed, and simulation comparison shows the effectiveness of the compensate method. The CarSim–MATLAB cosimulation shows that the proposed control strategy effectively makes the AGV follow the reference trajectory.

Highlights

Trajectory tracking control of autonomous ground vehicles (AGVs) plays an essential role in domestic and industrial use for increasing safety, accuracy, and efficiency demands, such as self-guiding uncrewed driving vehicles, platform supplying, and minesweeping [1]
Motivated by the above observations, this paper is aimed at giving a fixed-time observer-based control method, rendering the AGVs with yaw actuator dead zones to follow the reference trajectory
The results show that after considering the dead zone of the actuator, the improved fixed time disturbance observer (FTDO) method proposed is better than the conventional FTDO method because the compensation problem is considered in this paper

Summary

Introduction

Trajectory tracking control of autonomous ground vehicles (AGVs) plays an essential role in domestic and industrial use for increasing safety, accuracy, and efficiency demands, such as self-guiding uncrewed driving vehicles, platform supplying, and minesweeping [1]. Critical to the trajectory tracking problem of an AGV is its capability for accurate and reliable control to follow the desired trajectory by the planner [2]. The high dynamic nonlinearity, uncertainties and disturbances, and the mechanical limitations of the vehicle itself make the AGV trajectory tracking control challenging. Some existing works investigate the trajectory tracking problem of AGVs utilizing the kinematic model [3, 4]. The driving condition may be limited without reckoning the dynamics model. For this reason, the trajectory tracking control problem of a class of autonomous vehicles is investigated with parametric uncertainties, external disturbances, and overactuated features by introducing a novel adaptive hierarchical control framework with the linear matrix inequality technique [5]. A model predictive control law incorporating neural-dynamic optimization is introduced [9]

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