Observer design for unknown input nonlinear descriptor systems via convex optimization

This paper treats the design problem of full-order observers for nonlinear descriptor systems with unknown input (UI). Depending on the available knowledge on the UI dynamics, two cases are considered. First, a UI proportional observer (UIPO) is proposed when the spectral domain of the UI is unknown...

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Bibliographic Details
Published in:IEEE transactions on automatic control 2006-06, Vol.51 (6), p.1047-1052
Main Author: Koenig, D.
Format: Article
Language:English
Subjects:
Applied sciences
Asymptotic properties
Asymptotic stability
Automatic Control Engineering
Computer Science
Computer science
control theory
systems
Control theory. Systems
Design engineering
Design optimization
Dynamical systems
Exact sciences and technology
Frequency
Linear matrix inequalities
Linear matrix inequalities (LMIs)
Linear systems
Lipschitz nonlinear descriptor systems
Modelling and identification
Noise robustness
Nonlinear dynamics
Nonlinear systems
Nonlinearity
Observers
proportional integral observers
Spectra
Stability
State estimation
Sufficient conditions
Symmetric matrices
unknown input observers
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Summary:This paper treats the design problem of full-order observers for nonlinear descriptor systems with unknown input (UI). Depending on the available knowledge on the UI dynamics, two cases are considered. First, a UI proportional observer (UIPO) is proposed when the spectral domain of the UI is unknown. Second, a PIO is proposed when the spectral domain of the UI is in the low frequency range. Sufficient conditions for the existence and stability of such observers are given and proved. Based on the linear matrix inequality (LMI) approach, an algorithm is presented to compute the observer gain matrix that achieves the asymptotic stability objective. An example is included to illustrate the method.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2006.876807