Robust Filtering for Fuzzy Systems With Bounded Disturbances via Premise-Region-Dependent Event-Triggered Mechanisms

This article studies the problem of robust filtering for continuous-time Takagi-Sugeno (T-S) fuzzy systems with bounded external disturbances via premise-region-dependent event-triggered mechanisms (ETMs). First, attention is focused on the analysis and design of piecewise fuzzy filters (PFFs) witho...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems 2022-10, Vol.30 (10), p.4093-4101
Main Authors: Wang, Xiao-Lei, Yang, Guang-Hong
Format: Article
Language:English
Subjects:
Analytical models
Data models
Disturbances
Event triggered (ET)
Filtration
Fuzzy logic
fuzzy system
Fuzzy systems
Industries
Observers
piecewise fuzzy filter (PFF)
premise variables (PVs)
Regularization
Robustness (mathematics)
Technological innovation
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Summary:This article studies the problem of robust filtering for continuous-time Takagi-Sugeno (T-S) fuzzy systems with bounded external disturbances via premise-region-dependent event-triggered mechanisms (ETMs). First, attention is focused on the analysis and design of piecewise fuzzy filters (PFFs) without considering the ETMs. Then, based on the established PFF, ET PFF with time regularization is designed, such that the new augmented system is Zeno free and L_{\infty } stable, in which new ET conditions that depend on the different regions where the premise variables of the T-S model and the PFF are located are designed. Unlike the existing results, the designed observer gains in the absence of ETMs are also applicable to the case with ETMs, while the ones in the existing methods need to be redesigned. Finally, a simulation example is applied to verify the effectiveness of the proposed filtering scheme.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2021.3138646