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Erschienen in:
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2019 | OriginalPaper | Buchkapitel

8. Fuzzy Generalized \(\mathscr {H}_2\) Filtering for Nonlinear Discrete-Time Systems With Measurement Quantization

verfasst von : Ju H. Park, Hao Shen, Xiao-Heng Chang, Tae H. Lee

Erschienen in: Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals

Verlag: Springer International Publishing

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Abstract

This chapter investigates the problem of robust generalized \(\mathscr {H}_2\) filtering for uncertain nonlinear systems with the effects of dynamic quantization in the communication channel from the sensor to the filter based on T-S fuzzy model method. In the presence of dynamic quantization, we aim to design both full- and reduced-order generalized \(\mathscr {H}_2\) filters to asymptotically stabilize the filtering error systems and achieve generalized \(\mathscr {H}_2\) performances. In contrast with some published papers on the filtering design with dynamic quantization, the obtained design conditions are based on linear matrix inequalities (LMIs) which can be easily solved with the help of Matlab. Finally, a numerical example will be used to show the obtained design approaches of generalized \(\mathscr {H}_2\) filtering with quantization are effective.

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Vorheriges Kapitel Fuzzy Resilient Energy-to-Peak Filter Design for Continuous-Time Nonlinear Systems
Nächstes Kapitel Event-Triggered Dissipative Filtering for Networked Semi-Markov Jump Systems
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Metadaten
Titel
Fuzzy Generalized Filtering for Nonlinear Discrete-Time Systems With Measurement Quantization
verfasst von
Ju H. Park
Hao Shen
Xiao-Heng Chang
Tae H. Lee
Copyright-Jahr
2019
Buch
Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals

Print ISBN: 978-3-319-96201-6

Electronic ISBN: 978-3-319-96202-3

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-319-96202-3_8

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