Distributed fault estimation for delayed complex networks with Round-Robin protocol based on unknown input observer

被引：32

作者：

Gao, Ming ^{[1
]}

Zhang, Wenhua ^{[1
]}

Sheng, Li ^{[1
]}

Zhou, Donghua ^{[2
]}

机构：

[1] China Univ Petr East China, Coll Control Sci & Engn, Qingdao 266580, Peoples R China

[2] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2020年 / 357卷 / 13期

基金：

中国国家自然科学基金;

关键词：

TIME-VARYING SYSTEMS; DYNAMICAL NETWORKS; STATE ESTIMATION; SENSOR NETWORKS; SYNCHRONIZATION; DESIGN; SUBJECT;

D O I：

10.1016/j.jfranklin.2020.04.012

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 paper, the problem of distributed fault estimation is investigated for delayed complex networks with partially decoupled disturbances and sector-bounded nonlinearities. The data between each node and its neighboring ones of complex networks is transmitted through constrained networks, and the Round-Robin protocol is introduced to prevent data collisions over networks. An unknown input observer is designed for the ith node of complex networks by employing the information of adjacent nodes such that the disturbances are decoupled as much as possible. Moreover, the sufficient condition is derived to ensure the boundedness of the estimation error under the effect of disturbances that cannot be decoupled. The desired estimator gains can be calculated by solving linear matrix inequalities, and a numerical example is provided to illustrate the effectiveness of the developed methods. (C) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：8678 / 8702

页数：25

共 39 条

[11] Variance-Constrained Recursive State Estimation for Time-Varying Complex Networks With Quantized Measurements and Uncertain Inner Coupling [J].

Hu, Jun ;

Wang, Zidong ;

Liu, Guo-Ping ;

Zhang, Hongxu .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 31 (06) :1955-1967

[12] Joint state and fault estimation for time-varying nonlinear systems with randomly occurring faults and sensor saturations [J].

Hu, Jun ;

Wang, Zidong ;

Gao, Huijun .

AUTOMATICA, 2018, 97 :150-160

[13] On Unknown Input Observers for LPV Systems [J].

Ichalal, Dalil ;

Mammar, Said .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2015, 62 (09) :5870-5880

[14] Fault-tolerant passive synchronization for complex dynamical networks with Markovian jump based on sampled-data control [J].

Li, Jia ;

Ma, Yuechao ;

Fu, Lei .

NEUROCOMPUTING, 2019, 350 :20-32

[15] Adaptive Fault-Tolerant Synchronization Control of a Class of Complex Dynamical Networks With General Input Distribution Matrices and Actuator Faults [J].

Li, Xiao-Jian ;

Yang, Guang-Hong .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 28 (03) :559-569

[16] State estimation and fault reconstruction with integral measurements under partially decoupled disturbances [J].

Liu, Yang ;

Wang, Zidong ;

Zhou, Donghua .

IET CONTROL THEORY AND APPLICATIONS, 2018, 12 (10) :1520-1526

[17] Unknown input observer for LPV systems [J].

Marx, Benoit ;

Ichalal, Dalil ;

Ragot, Jose ;

Maquin, Didier ;

Mammar, Said .

AUTOMATICA, 2019, 100 :67-74

[18] Delay-dependent H∞ filtering for complex dynamical networks with time-varying delays in nonlinear function and network couplings [J].

Revathi, V. M. ;

Balasubramaniam, P. ;

Ratnavelu, K. .

SIGNAL PROCESSING, 2016, 118 :122-132

[19] Generalized Epidemic Mean-Field Model for Spreading Processes Over Multilayer Complex Networks [J].

Sahneh, Faryad Darabi ;

Scoglio, Caterina ;

Van Mieghem, Piet .

IEEE-ACM TRANSACTIONS ON NETWORKING, 2013, 21 (05) :1609-1620

[20] Fusion estimation for multi-rate linear repetitive processes under weighted try-once-discard protocol [J].

Shen, Yuxuan ;

Wang, Zidong ;

Shen, Bo ;

Alsaadi, Fawaz E. ;

Alsaadi, Fuad E. .

INFORMATION FUSION, 2020, 55 :281-291

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