Interval Observer Design for Uncertain Discrete-Time Polytopic Systems

This paper investigates interval estimation for discrete- time nonlinear systems described by polytopic models with measurable premise variables. By assuming that the disturbances and measurement noise are unknown but bounded, an interval observer design is proposed and sufficient convergence condit...

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Bibliographic Details
Published in2020 17th International Multi-Conference on Systems, Signals & Devices (SSD) pp. 85 - 90
Main Authors Sehli, Naima, Taarit, Kaouther Ibn, Raissi, Tarek, Ksouri, Moufida
Format Conference Proceeding
LanguageEnglish
Published IEEE 20.07.2020
Subjects
bounded error
Convergence
H∞ approach
interval observers
Lyapunov methods
Nonlinear systems
Observers
polytopic models
Robustness
Simulation
Time measurement
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Summary:This paper investigates interval estimation for discrete- time nonlinear systems described by polytopic models with measurable premise variables. By assuming that the disturbances and measurement noise are unknown but bounded, an interval observer design is proposed and sufficient convergence conditions are given by Lyapunov stability analysis. To improve the accuracy of interval estimation in order to attenuate energy-bounded unknown inputs such as disturbances, a direct method based on H_{\infty} approach and pole placement constraints is developed. A numerical example is given to show the effectiveness of the proposed methodoloay.
ISSN:2474-0446
DOI:10.1109/SSD49366.2020.9364217