Observer-Based Containment Control for a Class of Nonlinear Multiagent Systems With Uncertainties

被引:42
作者
Yang, Yang [1 ,2 ,3 ]
Tan, Jie [1 ,2 ]
Yue, Dong [1 ,2 ,3 ,4 ]
Xie, Xiangpeng [3 ,4 ]
Yue, Wenbin [5 ]
机构
[1] Nanjing Univ Posts & Telecommun, Coll Automat, Nanjing 210003, Peoples R China
[2] Nanjing Univ Posts & Telecommun, Coll Artificial Intelligence, Nanjing 210003, Peoples R China
[3] Nanjing Univ Posts & Telecommun, Jiangsu Engn Lab Big Data Anal & Control Act Dist, Nanjing 210003, Peoples R China
[4] Nanjing Univ Posts & Telecommun, Inst Adv Technol, Nanjing 210003, Peoples R China
[5] Brunel Univ London, Dept Comp Sci, Uxbridge UB8 3PH, Middx, England
来源
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2021年 / 51卷 / 01期
基金
中国国家自然科学基金;
关键词
Active disturbance rejection control (ADRC); backstepping technique; containment control; noise immunity; output-feedback; EXTENDED STATE OBSERVER; CONSENSUS TRACKING CONTROL; SPACECRAFT FORMATION; ATTITUDE TRACKING; DYNAMICS; DESIGN; DELAYS;
D O I
10.1109/TSMC.2018.2875515
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An observer-based containment control issue is addressed for a class of uncertain nonlinear multiagent systems with a directed topology via the active disturbance rejection control and backstepping techniques. A kind of nonlinear extended state observers (ESOs) based on fractional power functions is developed, and the estimations of extended states are utilized to compensate uncertain dynamics in real time. Compared with linear ESOs, the advantages of the ESOs in this paper lie in peaking reduction and better tolerance of measurement noise for the closed-loop system. Moreover, tracking differentiators are employed to avoid the explosion of complexity caused by repeated differentiations of nonlinear functions. It is proven that the containment errors of the followers converge to small neighborhoods of the origin and they are adjustable by suitable choice of parameters. Finally, two simulation examples, both practical and numerical ones, are shown to demonstrate the effectiveness of the proposed control approach.
引用
收藏
页码:588 / 600
页数:13
相关论文
共 50 条
[11]   Observer-Based Adaptive Control for a class of Nonlinear Chaotic Systems [J].
Liu, Yan-Jun ;
Li, Dong-Juan ;
Chen, C. L. Philip .
2011 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2011, :2011-2014
[12]   Adaptive observer-based control for a class of nonlinear stochastic systems [J].
Miao, Xiufeng ;
Li, Longsuo .
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, 2015, 92 (11) :2251-2260
[13]   Observer-Based Fixed-Time Adaptive Fuzzy Bipartite Containment Control for Multiagent Systems With Unknown Hysteresis [J].
Wu, Ying ;
Ma, Hui ;
Chen, Mou ;
Li, Hongyi .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2022, 30 (05) :1302-1312
[14]   Observer-based output feedback containment control of a class of nonlinear multi-agent systems via adaptive neural control method [J].
Xu, Tingru ;
Lyu, Jianting ;
Yang, Xinrong ;
Wang, Xin .
PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020), 2020, :1738-1743
[15]   Observer-based adaptive neural tracking control for a class of stochastic nonlinear systems [J].
Han, Yu-Qun ;
Zhu, Shan-Liang ;
Duan, De-Yu ;
Chu, Lei ;
Xiong, Peng-Cheng ;
Yang, Shu-Guo .
INTERNATIONAL JOURNAL OF CONTROL, 2021, 94 (05) :1344-1354
[16]   Distributed Containment Control for Nonlinear Stochastic Multiagent Systems [J].
Li, Kuo ;
Hua, Changchun ;
Guan, Xinping .
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 51 (06) :3361-3370
[17]   Perturbation observer-based adaptive passive control for nonlinear systems with uncertainties and disturbances [J].
Yang, B. ;
Jiang, L. ;
Zhang, C. K. ;
Sang, Y. Y. ;
Yu, T. ;
Wu, Q. H. .
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2018, 40 (04) :1223-1236
[18]   Output-Based Containment Control for Uncertain Nonaffine Nonlinear Multiagent Systems [J].
Yang, Yang ;
Tan, Jie ;
Yue, Dong ;
Tian, Yu-Chu ;
Xue, Yusheng .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (10) :5992-6002
[19]   Observer-Based adaptive neural inverse optimal consensus control of nonlinear multiagent systems [J].
Lu, Xinyi ;
Wang, Fang ;
Liu, Zhi ;
Chen, L. Philip .
JOURNAL OF THE FRANKLIN INSTITUTE, 2023, 360 (09) :6296-6320
[20]   Disturbance observer-based consensus tracking for nonlinear multiagent systems with switching topologies [J].
Ai, Xiaolin ;
Yu, Jianqiao ;
Jia, Zhenyue ;
Yang, Di ;
Xu, Xuan ;
Shen, Yuanchuan .
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2018, 28 (06) :2144-2160