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2019 | OriginalPaper | Chapter

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

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

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

Publisher: 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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previous chapter Fuzzy Resilient Energy-to-Peak Filter Design for Continuous-Time Nonlinear Systems
next chapter Event-Triggered Dissipative Filtering for Networked Semi-Markov Jump Systems
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Metadata
Title
Fuzzy Generalized Filtering for Nonlinear Discrete-Time Systems With Measurement Quantization
Authors
Ju H. Park
Hao Shen
Xiao-Heng Chang
Tae H. Lee
Copyright Year
2019
Book
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 Year: 2019

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