Distributed fuzzy adaptive consensus for high-order multi-agent systems with an imprecise communication topology structure

被引：42

作者：

Chen, Jiaxi ^{[1
]}

Li, Junmin ^{[1
]}

Yuan, Xinxin ^{[1
]}

机构：

[1] Xidian Univ, Sch Math & Stat, Xian 710126, Peoples R China

来源：

FUZZY SETS AND SYSTEMS | 2021年 / 402卷

关键词：

Adaptive control; Consensus algorithm; Formation control; Imprecise communication topology; Multi-agent system; Takagi-Sugeno fuzzy model; UNKNOWN CONTROL DIRECTIONS; TRACKING CONTROL; LEADER; AGENTS;

D O I：

10.1016/j.fss.2020.03.018

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this study, we consider the consensus problem for a high-order multi-agent systems (MASs) with an imprecise communica-tion topology structure described by the Takagi-Sugeno fuzzy model. A distributed adaptive control protocol is proposed for the consensus problem comprising MASs with unknown parameters and input disturbances. The proposed protocol can guarantee that the consensus errors asymptotically approach zero under the conditions that the communication topology is fuzzy union connected and the dynamics of the leader are unknown to any agent among the followers. Furthermore, the proposed algorithm is extended to solve the formation control problem for MASs. Sufficient conditions are provided for the consensus and formation problems for MASs based on Lyapunov stability theory. Finally, three simulation examples are presented to illustrate the effectiveness of the proposed control protocol. (C) 2020 Elsevier B.V. All rights reserved.

引用

页码：1 / 15

页数：15

共 41 条

[1] Fuzzy Observed-Based Adaptive Consensus Tracking Control for Second-Order Multiagent Systems With Heterogeneous Nonlinear Dynamics [J].

Chen, C. L. Philip ;

Ren, Chang-E ;

Du, Tao .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2016, 24 (04) :906-915

[2] Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks [J].

Chen, C. L. Philip ;

Wen, Guo-Xing ;

Liu, Yan-Jun ;

Wang, Fei-Yue .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 25 (06) :1217-1226

[3] Global Fuzzy Adaptive Consensus Control of Unknown Nonlinear Multiagent Systems [J].

Chen, Jiaxi ;

Li, Junmin ;

Yuan, Xinxin .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2020, 28 (03) :510-522

[4] Fuzzy adaptive iterative learning coordination control of second-order multi-agent systems with imprecise communication topology structure [J].

Chen, Jiaxi ;

Li, Junmin .

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2018, 49 (03) :546-556

[5]

Chen JX, 2017, 2017 6TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS (DDCLS), P54, DOI 10.1109/DDCLS.2017.8068044

[6]

Chen JX, 2017, CHIN CONT DECIS CONF, P4465, DOI 10.1109/CCDC.2017.7979285

[7] Consensus of second-order nonlinear multi-agent systems under state-controlled switching topology [J].

Chen, Kairui ;

Wang, Junwei ;

Zhang, Yun ;

Liu, Zhi .

NONLINEAR DYNAMICS, 2015, 81 (04) :1871-1878

[8] Adaptive Consensus of Multi-Agent Systems With Unknown Identical Control Directions Based on A Novel Nussbaum-Type Function [J].

Chen, Weisheng ;

Li, Xiaobo ;

Ren, Wei ;

Wen, Changyun .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2014, 59 (07) :1887-1892

[9] Formation-containment control for high-order linear time-invariant multi-agent systems with time delays [J].

Dong, Xiwang ;

Li, Qingdong ;

Ren, Zhang ;

Zhong, Yisheng .

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2015, 352 (09) :3564-3584

[10] Global leader-following consensus of nonlinear multi-agent systems with unknown control directions and unknown external disturbances [J].

Fan, Ming-Can ;

Wu, Yue .

APPLIED MATHEMATICS AND COMPUTATION, 2018, 331 :274-286

← 1 2 3 4 5 →