Consensus of multi-Agent systems with one-Sided lipschitz nonlinearity via nonidentical double event-Triggered control subject to deception attacks

被引：14

作者：

Wang, Maolin ^{[1
]}

Yang, Xinsong ^{[1
]}

Mao, Shuoyu ^{[1
]}

Yiu, Ka Fai Cedric ^{[2
]}

Park, Ju H. ^{[3
]}

机构：

[1] Sichuan Univ, Coll Elect & Informat Engn, Chengdu 610065, Peoples R China

[2] Hong Kong Polytech Univ, Dept Appl Math, Hong Kong, Peoples R China

[3] Yeungnam Univ, Dept Elect Engn, Kyongsan 38541, South Korea

来源：

JOURNAL OF THE FRANKLIN INSTITUTE | 2023年 / 360卷 / 09期

基金：

新加坡国家研究基金会;

关键词：

LEADER-FOLLOWING CONSENSUS; DISTRIBUTED CONSENSUS; TRACKING CONTROL; NEURAL-NETWORKS; SYNCHRONIZATION;

D O I：

10.1016/j.jfranklin.2023.04.028

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

As for the multi-agent systems (MASs) with time-varying switching subject to deception attacks, the leader-following consensus problem is studied in this article. The one-sided Lipschitz (OSL) condition is utilized for the nonlinear functions, which makes the results more general and relaxed than those obtained by Lipschitz condition. The nonidentical double event-triggering mechanisms (ETMs) are adopted for only a fraction of agents, and each agent transmits the data according to its own necessity. Semi-Markov process modeling with time-varying switching probability is adopted for switching topology and deception attacks occurring in transmission channel are considered. By using the cumulative distribution function (CDF) and the linear matrix inequality (LMI) technology, sufficient conditions for MASs to achieve consensus in mean square are obtained. An effective algorithm is presented to obtain the event -based control gains. The merits of the proposed control scheme are demonstrated via a simulation example.& COPY; 2023 The Franklin Institute. Published by Elsevier Inc. All rights reserved.

引用

页码：6275 / 6295

页数：21

共 47 条

[1]

Abbaszadeh M, 2010, P AMER CONTR CONF, P5284

[2] Adaptive Distributed Consensus Control of One-Sided Lipschitz Nonlinear Multiagents [J].

Agha, Rizwana ;

Rehan, Muhammad ;

Ahn, Choon Ki ;

Mustafa, Ghulam ;

Ahmad, Sohaira .

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2019, 49 (03) :568-578

[3] Multi-Agent System in Urban Traffic Signal Control [J].

Balaji, P. G. ;

Srinivasan, D. .

IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 2010, 5 (04) :43-51

[4] Event-triggered average consensus control for discrete-time multi-agent systems [J].

Chen, X. ;

Hao, F. .

IET CONTROL THEORY AND APPLICATIONS, 2012, 6 (16) :2493-2498

[5] Observer-based consensus tracking of multi-agent systems with one-sided Lipschitz nonlinearity [J].

Chu, Hongjun ;

Liu, Xiaocheng ;

Zhang, Weidong ;

Cai, Yunze .

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2016, 353 (07) :1594-1614

[6] Event-Based Consensus for a Class of Nonlinear Multi-Agent Systems With Sequentially Connected Topology [J].

Cui, Ying ;

Liu, Yurong ;

Zhang, Wenbing ;

Alsaadi, Fuad E. .

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2018, 65 (10) :3506-3518

[7] Event-triggered leader-following consensus for multi-agent systems with semi-Markov switching topologies [J].

Dai, Jiangtao ;

Guo, Ge .

INFORMATION SCIENCES, 2018, 459 :290-301

[8] Exponential consensus of non-linear multi-agent systems with semi-Markov switching topologies [J].

Dai, Jiangtao ;

Guo, Ge .

IET CONTROL THEORY AND APPLICATIONS, 2017, 11 (18) :3363-3371

[9] Multi-Agent System for Distributed Management of Microgrids [J].

Eddy, Y. S. Foo. ;

Gooi, H. B. ;

Chen, S. X. .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2015, 30 (01) :24-34

[10] Distributed consensus of the nonlinear second-order multi-agent systems via mixed intermittent protocol [J].

Guo, Wanli ;

Xiao, Haijun .

NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2018, 30 :189-198

← 1 2 3 4 5 →