Adaptive NN-based finite-time trajectory tracking control of wheeled robotic systems

被引:12
作者
Jin, Xiaozheng [1 ,2 ,3 ]
Zhao, Zhiye [1 ,2 ,3 ]
Wu, Xiaoming [1 ,2 ,3 ]
Chi, Jing [4 ]
Deng, Chao [5 ]
机构
[1] Qilu Univ Technol, Shandong Acad Sci, Sch Comp Sci & Technol, Jinan 250353, Shandong, Peoples R China
[2] Natl Supercomp Ctr Jinan, Shandong Comp Sci Ctr, Jinan 250014, Shandong, Peoples R China
[3] Shandong Lab Comp Networks, Jinan 250014, Shandong, Peoples R China
[4] Shandong Univ Finance & Econ, Dept Comp Sci & Technol, Jinan 250014, Shandong, Peoples R China
[5] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore, Singapore
基金
中国国家自然科学基金;
关键词
Robotic systems; Neural networks; Adaptive finite-time control; Trajectory tracking; SLIDING MODE CONTROL; MOBILE ROBOTS; MULTIAGENT SYSTEMS; VEHICLE; SYNCHRONIZATION; STABILITY; OBSERVER;
D O I
10.1007/s00521-021-06021-7
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The trajectory tracking and finite-time control problems of wheeled robotic systems with nonlinear dynamics and uncertainties are investigated in this paper. An adaptive neural network (NN)-based control technique is developed to deal with the nonlinearities and uncertainties. Then, finite-time dynamic control and kinematic control schemes are constructed on the basis of the adaptive estimations to remedy the negative influence of uncertainties and nonlinearities. Specific forward and azimuthal angular velocities are developed by using NN-based kinematic control schemes to obtain the finite-time tracking of the desired position trajectory for the wheeled robotic system. Furthermore, the asymptotic tracking of the specific forward and azimuthal angular velocities is further achieved based on the finite-time dynamic control schemes with uncertainties and nonlinear dynamics. The efficacy of the developed finite-time tracking control approach is substantiated by a robotic system.
引用
收藏
页码:5119 / 5133
页数:15
相关论文
共 51 条
[1]  
[Anonymous], 1952, Inequalities, Cambridge
[2]   A robust adaptive fuzzy variable structure tracking control for the wheeled mobile robot: Simulation and experimental results [J].
Begnini, Mauricio ;
Bertol, Douglas Wildgrube ;
Martins, Nardenio Almeida .
CONTROL ENGINEERING PRACTICE, 2017, 64 :27-43
[3]   Finite-time stability of continuous autonomous systems [J].
Bhat, SP ;
Bernstein, DS .
SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2000, 38 (03) :751-766
[4]   Adaptive finite-time control of a class of non-triangular nonlinear systems with input saturation [J].
Cai, Mingjie ;
Xiang, Zhengrong .
NEURAL COMPUTING & APPLICATIONS, 2018, 29 (07) :565-576
[5]   Robust hierarchical sliding mode control of a two-wheeled self-balancing vehicle using perturbation estimation [J].
Chen, Long ;
Wang, Hai ;
Huang, Yunzhi ;
Ping, Zhaowu ;
Yu, Ming ;
Zheng, Xuefeng ;
Ye, Mao ;
Hu, Youhao .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2020, 139
[6]   Adaptive robust finite-time neural control of uncertain PMSM servo system with nonlinear dead zone [J].
Chen, Qiang ;
Ren, Xuemei ;
Na, Jing ;
Zheng, Dongdong .
NEURAL COMPUTING & APPLICATIONS, 2017, 28 (12) :3725-3736
[8]   Distributed Resilient Observer-Based Fault-Tolerant Control for Heterogeneous Multiagent Systems Under Actuator Faults and DoS Attacks [J].
Deng, Chao ;
Wen, Changyun .
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2020, 7 (03) :1308-1318
[9]   Distributed adaptive fault-tolerant control approach to cooperative output regulation for linear multi-agent systems [J].
Deng, Chao ;
Yang, Guang-Hong .
AUTOMATICA, 2019, 103 :62-68
[10]   Finite-Time Synchronization of a Class of Second-Order Nonlinear Multi-Agent Systems Using Output Feedback Control [J].
Du, Haibo ;
He, Yigang ;
Cheng, Yingying .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2014, 61 (06) :1778-1788