Distributed neuroadaptive fault-tolerant sliding-mode control for 2-D plane vehicular platoon systems with spacing constraints and unknown direction faults

被引:100
作者
Guo, Xiang-Gui [1 ,2 ]
Xu, Wei-Dong [1 ,2 ]
Wang, Jian-Liang [3 ]
Park, Ju H. [4 ]
机构
[1] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing Engn Res Ctr Ind Spectrum Imaging, Beijing 100083, Peoples R China
[2] Univ Sci & Technol Beijing, Shunde Grad Sch, Foshan 528000, Peoples R China
[3] Beihang Univ, Hangzhou Innovat Inst, Hangzhou 310051, Peoples R China
[4] Yeungnam Univ, Dept Elect Engn, Kyongsan 38541, South Korea
基金
中国国家自然科学基金; 新加坡国家研究基金会; 浙江省自然科学基金;
关键词
Fault-tolerant control (FTC); Sliding-mode control (SMC); Two-dimensional (2-D) multi-lane vehicle fusion; Spacing constraints; Nussbaum function; Unknown direction actuator faults; ADAPTIVE NEURAL-CONTROL; NONLINEAR-SYSTEMS;
D O I
10.1016/j.automatica.2021.109675
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, neuroadaptive fault-tolerant control of nonlinear vehicular platoon systems subject to unknown direction actuator faults, unmodeled dynamics, and external disturbances is investigated. A vehicle model considering the influence of velocity direction deflection angle on vehicle position is proposed on a two-dimensional (2-D) plane to realize multi-lane vehicle fusion. Then, in order to avoid collisions and maintain communication connection, the method of asymmetric barrier Lyapunov function (BLF) is adopted to eliminate the unfavorable assumption on spacing constraints in using symmetric BLF in the existing result. Nussbaum function is adopted to attenuate the negative effects caused by unknown direction actuator faults. Furthermore, by combining sliding-mode control (SMC) techniques with radial basis function neural network (RBFNN), a novel neuroadaptive fault-tolerant control scheme with minimal learning parameters is designed to not only guarantee the finite-time stability of the whole vehicular platoon but also tolerate the unknown direction actuator faults. Finally, simulation results show the effectiveness and advantages of the proposed scheme. (C) 2021 The Author(s). Published by Elsevier Ltd.
引用
收藏
页数:8
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