容错
控制(管理)
路径(计算)
跟踪(教育)
计算机科学
控制理论(社会学)
实时计算
控制工程
分布式计算
工程类
人工智能
计算机网络
心理学
教育学
作者
Ruinan Chen,Jie Hu,Minchao Zhang,Linglei Zhu,Xinkai Zhong
标识
DOI:10.1177/09544062231223852
摘要
Signal delay, execution deviation and reference model mismatch are common faults in autonomous vehicles, resulting in reduced path tracking control performance. To improve the path tracking performance of autonomous vehicles under fault conditions, this paper proposes a hybrid fault-tolerant (HFT) path tracking control approach, in which passive fault-tolerant path tracking control and fault observer-based hybrid active fault-tolerant path tracking control are introduced. The probable usual errors in path tracking are first examined and analyzed, together with the vehicle kinematic model and a typical autonomous driving system. Then, a slide-mode-based passive fault-tolerant path tracking controller is designed and integrated with a fault observer to create a hybrid active fault-tolerant controller. Finally, simulations and experiments are conducted, and the results demonstrate that our proposal is effective. After convergence of the fault observations, the lateral tracking error is less than 0.2m and the root mean square of the tracking error is 44% smaller than the LQR approach.
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