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Erschienen in: Granular Computing 1/2020

13.10.2018 | Original Paper

Robust functional observer for stabilising uncertain fuzzy systems with time-delay

verfasst von: Syed Imranul Islam, Peng Shi, Cheng-Chew Lim

Erschienen in: Granular Computing | Ausgabe 1/2020

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Abstract

This paper presents a new technique for stabilising a Takagi–Sugeno (T-S) fuzzy system with time-delay and uncertainty. A robust fuzzy functional observer is employed to design a controller when the system states are not measurable. The model uncertainty is norm bounded, and the time-delay is time-varying but bounded. The parallel distributed compensation method is applied for defining the fuzzy functional observer to design this controller. The proposed procedure reduces the observer order to the dimension of the control input. Improved stability conditions are provided for the observer compared with the existing results of functional observer-based stabilisation of T-S fuzzy models. Lyapunov–Krasovskii functionals are used to construct delay-dependent stability conditions as linear matrix inequalities. The solution of these inequalities is used for calculating the observer parameters. The sensitivity of the estimation error to the model uncertainty is reduced by minimising the \(L_2\) gain. The new design method developed is illustrated and verified using two examples.

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Metadaten
Titel
Robust functional observer for stabilising uncertain fuzzy systems with time-delay
verfasst von
Syed Imranul Islam
Peng Shi
Cheng-Chew Lim
Publikationsdatum
13.10.2018
Verlag
Springer International Publishing
Erschienen in
Granular Computing / Ausgabe 1/2020
Print ISSN: 2364-4966
Elektronische ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-018-0138-x

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