Path-Tracking Considering Yaw Stability With Passivity-Based Control for Autonomous Vehicles
Path-Tracking Considering Yaw Stability With Passivity-Based Control for Autonomous Vehicles
复制标题
考虑偏航稳定性和基于无源控制的自动驾驶车辆的路径跟踪
DOI：
10.1109/tits.2021.3085713
复制
发表时间：
2022-07
影响因子：
8.5
通讯作者：
Yuexuan Wang
中科院分区：
文献类型：
--
作者：
Yan Ma;Jian Chen;Junmin Wang;Yanchuan Xu;Yuexuan Wang
在本文中，一种新的基于无源性的控制方法，旨在提高自主车辆在执行路径跟踪任务的鲁棒性和稳定性。端口哈密顿模型是一种特殊的几何结构，它提供了一个系统的和有见地的框架来描述许多物理系统从能量的角度来看。基于无源性的控制建立了一个新的和简单的结构来实现路径跟踪任务的端口哈密顿结构。首先，将路径跟踪误差系统转化为一个带有扰动的端口哈密顿系统。利用能量成形方法保证了系统的渐近稳定性，并给出了闭环路径跟踪误差系统的稳定性证明。所提出的实时无源控制器直接依赖于无源输出，对负载变化引起的参数不确定性具有鲁棒性。此外，当转向角饱和时，转向控制的控制性能将下降。引入横摆力矩控制以提高行驶安全性。在车轮扭矩分配中，设计了一种基于优化的控制分配方法，使轮胎载荷之和最小，并使其更均匀地分配到每个轮胎上。最后，在MATLAB/Simulink和CarSim联合仿真平台上进行仿真，验证了所设计策略在不同工况下的有效性。
In this paper, a new passivity-based control approach is designed to improve the robustness and stability of autonomous vehicles in performing path-tracking tasks. A port-Hamiltonian model is a special geometric structure and provides a systematic and insightful framework to describe many physical systems from an energy perspective. The passivity-based control establishes a new and simple structure to achieve the path-tracking task by the port-Hamiltonian structure. Firstly, the path-tracking error system is transformed into a port-Hamiltonian system with the perturbation. The energy-shaping method is utilized to ensure the asymptotic stability, and the stability proof of the closed-loop, path-tracking error system is given. The proposed real-time, passivity-based controller is directly dependent on the passive outputs, which is robust to parameter uncertainties caused by load changes. Moreover, the control performance of steering control will be degraded when the steering angle is saturated. The yaw-moment control is introduced to enhance the driving safety. In the wheel torque distribution, an optimization-based control allocation is designed to minimize the sum of tire loads and to make them more evenly distributed to each tire. Finally, simulations are implemented in MATLAB/Simulink and CarSim co-simulation to demonstrate the effectiveness of the designed strategy under different driving conditions.