Synchronization of Markovian complex networks with input mode delay and Markovian directed communication via distributed dynamic event-triggered control

被引：84

作者：

Zhao, Can ^{[1
]}

Zhong, Shouming ^{[1
]}

Zhong, Qishui ^{[2
,3
]}

Shi, Kaibo ^{[4
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Sichuan, Peoples R China

[2] Univ Elect Sci & Technol China, Sch Aeronaut & Astronaut, Chengdu 611731, Sichuan, Peoples R China

[3] Inst Elect & Informat Engn UESTC Guangdong, Dongguan 523808, Guangdong, Peoples R China

[4] Chengdu Univ, Sch Informat Sci & Engn, Chengdu 610106, Sichuan, Peoples R China

来源：

NONLINEAR ANALYSIS-HYBRID SYSTEMS | 2020年 / 36卷

基金：

中国国家自然科学基金;

关键词：

Complex networks; Synchronization; Markov switching; Event-triggered control; MULTIAGENT SYSTEMS; STATE ESTIMATION; NEURAL-NETWORKS; STABILITY; PERTURBATIONS; CONSENSUS;

D O I：

10.1016/j.nahs.2020.100883

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 study, distributed dynamic event-triggered controller containing Markov switching topologies is proposed in Markovian Complex Networks (MCNs). It is proved that the Zeno-behavior is avoided. Considering that the time delay and the controller vary with different modes in practical applications, two terms of the controller are designed to contain Markov switching. And mode-dependent Lyapunov-Krasovskii functions (LKFs) are constructed, whereby the time-varying delay with Markov switching in the controller is perfectly processed. And by constructing a pair of LKFs, some summation terms containing the transition probability are eliminated. In addition, two synchronization criteria for MCNs with input mode delay and Markovian directed communication are established. Finally, numerical simulations are given to illustrate the effectiveness of the proposed method. (c) 2020 Elsevier Ltd. All rights reserved.

引用

页数：14

共 44 条

[1]

[Anonymous], ARXIV190306368

[2]

[Anonymous], J FRANKLIN I B

[3]

[Anonymous], 2018, IEEE T CYBERN

[4] Stability and Hopf bifurcation of controlled complex networks model with two delays [J].

Cao, Jinde ;

Guerrini, Luca ;

Cheng, Zunshui .

APPLIED MATHEMATICS AND COMPUTATION, 2019, 343 :21-29

[5] Nonstationary l2 - l∞ filtering for Markov switching repeated scalar nonlinear systems with randomly occurring nonlinearities [J].

Cheng, Jun ;

Zhan, Yang .

APPLIED MATHEMATICS AND COMPUTATION, 2020, 365 (365)

[6] Static output feedback control of switched systems with quantization: A nonhomogeneous sojourn probability approach [J].

Cheng, Jun ;

Park, Ju H. ;

Zhao, Xudong ;

Cao, Jinde ;

Qi, Wenhai .

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2019, 29 (17) :5992-6005

[7] Hidden Markov Model-Based Nonfragile State Estimation of Switched Neural Network With Probabilistic Quantized Outputs [J].

Cheng, Jun ;

Park, Ju H. ;

Cao, Jinde ;

Qi, Wenhai .

IEEE TRANSACTIONS ON CYBERNETICS, 2020, 50 (05) :1900-1909

[8] An Event-Based Asynchronous Approach to Markov Jump Systems With Hidden Mode Detections and Missing Measurements [J].

Cheng, Jun ;

Ahn, Choon Ki ;

Karim, Hamid Reza ;

Cao, Jinde ;

Qi, Wenhai .

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2019, 49 (09) :1749-1758

[9] Sampled-data reliable control for T-S fuzzy semi-Markovian jump system and its application to single-link robot arm model [J].

Cheng, Jun ;

Wang, Bo ;

Park, Ju H. ;

Kang, Wei .

IET CONTROL THEORY AND APPLICATIONS, 2017, 11 (12) :1904-1912

[10] Novel delay-dependent robust stability criteria for neutral systems with mixed time-varying delays and nonlinear perturbations [J].

Cheng, Jun ;

Zhu, Hong ;

Zhong, Shouming ;

Li, Guihua .

APPLIED MATHEMATICS AND COMPUTATION, 2013, 219 (14) :7741-7753

← 1 2 3 4 5 →