Optimal Path Tracking Control Based on Online Modeling for Autonomous Vehicle With Completely Unknown Parameters

作     者：Ji, Yuan Zhang, Junzhi Lv, Chen He, Chengkun Chen, Hao Han, Jinheng Hou, Xiaohui 

作者机构：Tsinghua Univ Sch Vehicle & Mobil Beijing 100084 Peoples R China Tsinghua Univ State Key Lab Intelligent Green Vehicle & Mobil Beijing 100084 Peoples R China Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore 639798 Singapore Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China 

出 版 物：《IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS》 (IEEE Trans. Intell. Transp. Syst.)

年 卷 期：2023年第24卷第12期

页      面：15207-15218页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0814[工学-土木工程] 0823[工学-交通运输工程] 

基　　金：National Natural Science Foundation of China 

主　　题：Path tracking online modelling adaptive dynamic programming fault-tolerant 

摘      要：Reliable path tracking control (PTC) method is essential for autonomous driving. However, existing PTC methods count on prior vehicle parameters to achieve good performance. This paper presents an optimal PTC method without requiring any prior vehicle parameters based on online modeling with strict parameter convergence ability. First, we build a virtual optimal control problem using adaptive dynamic programming (ADP) scheme to guide the data collection and solve two characteristic matrices containing parameter information. Then, the model construction method is derived using the solved matrices and the optimal PTC method is constructed using the constructed model. Finally, a fault-tolerant control scheme is further designed using the constructed model and the online modeling ability of the proposed method. The effectiveness of the proposed method is validated through co-simulation between Matlab/Simulink and high-fidelity vehicle dynamic simulation software CarSim (R) under both fault-free and fault-tolerant situations.