Fault-Tolerant Synchronization Control for Complex Networks by an Average Observer Approach

This article is dedicated to a fault-tolerant synchronization control method of complex networks (CNs) via an average observer. A projected operator matrix is constructed to reduce the dimension of CNs by clustering and aggregation. An average observer with derivative and integral terms is built to estimate unknown elements with high estimation accuracy. The fault-tolerant controller is a composite form of state-feedback and the estimated faults. Sufficient criterions are set up to guarantee the uniformly ultimately bounded synchronization of the resultant close-loop system. Finally, an example is simulated to deliver the effectiveness of the proposed approach.

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Publication Details

Journal
IEEE Transactions on Systems Man and Cybernetics Systems
Published
2025-08-26
DOI
https://doi.org/10.1109/tsmc.2025.3598020
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
0.00

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article

Fault-Tolerant Synchronization Control for Complex Networks by an Average Observer Approach

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Neural Networks Stability and Synchronization
article

Fault-Tolerant Synchronization Control for Complex Networks by an Average Observer Approach

Chen Wang, Tingwen Huang, Wen Qin, Mouquan Shen, Qing-Guo Wang
article en

Abstract

This article is dedicated to a fault-tolerant synchronization control method of complex networks (CNs) via an average observer. A projected operator matrix is constructed to reduce the dimension of CNs by clustering and aggregation. An average observer with derivative and integral terms is built to estimate unknown elements with high estimation accuracy. The fault-tolerant controller is a composite form of state-feedback and the estimated faults. Sufficient criterions are set up to guarantee the uniformly ultimately bounded synchronization of the resultant close-loop system. Finally, an example is simulated to deliver the effectiveness of the proposed approach.

IEEE Transactions on Systems Man and Cybernetics SystemsVol. 55(11)
Nanjing Tech University (CN), Shenzhen University (CN), Shenzhen Technology University (CN), Wuhan University of Science and Technology (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 75%
Neural Networks Stability and Synchronization
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