Partial‐node‐based resilient set‐membership filtering for output‐coupled complex networks with event‐triggered mechanisms

Author:

Lin Ming1,Shen Qi1,Liu Chang12,Peng Hui1,Xu Yong1ORCID

Affiliation:

1. Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control, and Guangdong‐Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control, School of Automation Guangdong University of Technology Guangzhou China

2. Pazhou Lab Guangzhou China

Abstract

AbstractThis paper studies the resilient set‐membership filtering for discrete‐time nonlinear complex networks with output‐coupled topologies. An event‐triggered mechanism (ETM) is employed to save communication resources from the sensor to the filter. A resilient set‐membership filter (RSMF) handles unknown bounded uncertainty, resists the gain perturbation and makes the estimation errors to a certain ellipsoid region. Sufficient conditions for the existence of the RSMF are derived using mathematical induction techniques. The filter gain can be determined on the basis of solving a specific set of recursive matrix inequalities. Then, by optimizing the constrained ellipsoid of the estimation error, the optimized filtering performance is ensured. Finally, a numerical example is given to demonstrate the effectiveness of the proposed RSMF.

Funder

Special Project for Research and Development in Key areas of Guangdong Province

China Postdoctoral Science Foundation

National Natural Science Foundation of China

Publisher

Wiley

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