JOURNAL ARTICLE

Adaptive Event-Triggered Fuzzy $H_{\infty }$ Filter Design for Nonlinear Networked Systems

Xin ZhaoChong LinBing ChenQing‐Guo WangZhongjing Ma

Year: 2019 Journal:   IEEE Transactions on Fuzzy Systems Vol: 28 (12)Pages: 3302-3314   Publisher: Institute of Electrical and Electronics Engineers

Abstract

This article studies the problem of the fuzzy H filter design for nonlinear networked control systems through eventtriggered communication (ETC) scheme. First, a novel adaptive ETC scheme is given to determine whether the sampled measurement output should be released to communication network or not. Consequently, less communication resources are occupied under the desired H performance. Second, augmented fuzzy lineintegral Lyapunov function is introduced in the H performance analysis of filter error systems, such that the information of time derivative of membership functions are fully considered to reduce the conservativeness of networked fuzzy filter design. Different from the existing results, the upper bounds of time derivative of membership functions need not to be known prior. Third, the resulting filter error system is modeled as time-delay system under ETC mechanism and asynchronous premise in a unified framework. As a result, applying Lyapunov theory and inequality technique, new sufficient condition is obtained to meet the H performance for the filter error systems. Further, the corresponding filter and event-triggering parameters are codesigned and solved by a set of linear matrix inequalities. Finally, two examples are offered to demonstrate the advantage of the proposed method.

Keywords:
Filter (signal processing) Lyapunov function Computer science Fuzzy logic Filter design Fuzzy control system Control theory (sociology) Mathematics Nonlinear system Artificial intelligence Control (management)

Metrics

35
Cited By
2.97
FWCI (Field Weighted Citation Impact)
39
Refs
0.92
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Stability and Control of Uncertain Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Neural Networks Stability and Synchronization
Physical Sciences →  Computer Science →  Computer Networks and Communications
Stability and Controllability of Differential Equations
Physical Sciences →  Engineering →  Control and Systems Engineering
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