# Robust identification of parasitic feedback disturbances for linear lumped parameter systems

Vyacheslav Maksimov; Luciano Pandolfi

International Journal of Applied Mathematics and Computer Science (2001)

- Volume: 11, Issue: 4, page 835-858
- ISSN: 1641-876X

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topMaksimov, Vyacheslav, and Pandolfi, Luciano. "Robust identification of parasitic feedback disturbances for linear lumped parameter systems." International Journal of Applied Mathematics and Computer Science 11.4 (2001): 835-858. <http://eudml.org/doc/207534>.

@article{Maksimov2001,

abstract = {We study the problem of identification of an input to a linear finite-dimensional system. We assume that the input has a feedback form, which is related to a problem often encountered in fault detection. The method we use is to embed the identification problem in a class of inverse problems of dynamics for controlled systems. Two algorithms for identification of a feedback matrix based on the method of feedback control with a model are constructed. These algorithms are stable with respect to noise-corrupted observations and computational errors.},

author = {Maksimov, Vyacheslav, Pandolfi, Luciano},

journal = {International Journal of Applied Mathematics and Computer Science},

keywords = {feedback control; fault detection; input identification},

language = {eng},

number = {4},

pages = {835-858},

title = {Robust identification of parasitic feedback disturbances for linear lumped parameter systems},

url = {http://eudml.org/doc/207534},

volume = {11},

year = {2001},

}

TY - JOUR

AU - Maksimov, Vyacheslav

AU - Pandolfi, Luciano

TI - Robust identification of parasitic feedback disturbances for linear lumped parameter systems

JO - International Journal of Applied Mathematics and Computer Science

PY - 2001

VL - 11

IS - 4

SP - 835

EP - 858

AB - We study the problem of identification of an input to a linear finite-dimensional system. We assume that the input has a feedback form, which is related to a problem often encountered in fault detection. The method we use is to embed the identification problem in a class of inverse problems of dynamics for controlled systems. Two algorithms for identification of a feedback matrix based on the method of feedback control with a model are constructed. These algorithms are stable with respect to noise-corrupted observations and computational errors.

LA - eng

KW - feedback control; fault detection; input identification

UR - http://eudml.org/doc/207534

ER -

## References

top- Blizorukova M.S. and Maksimov V.I. (1997): On the reconstruction of an extremal input in a system with hereditary. - Vestnik PGTU. Funct. Diff. Eqns., Vol.4, No.4, pp.51-61 (in Russian).
- Fagnani F. and Pandolfi L. (2000): A singular perturbation approach to an input identification problem. - Rapp. Interno n. 4, Dipartimento di Matematica, Politecnico di Torino. Zbl1018.93016
- Kryazhimskii A.V. (1999): Convex optimization via feedbacks. - SIAM J. Contr. Optim., Vol.37, No.1, pp.278-302. Zbl0917.90256
- Kryazhimskii A.V. and Osipov Yu.S. (1987): To a regularization of a convex extremal problem within accurately given constraints. An application to an optimal control problem with state constraints. In: Some Methods of Positional and Program Control (A.I. Korotkii and V.I. Maksimiv, Eds.). - Academic Press, Sverdlovsk, pp.34-54 (in Russian).
- Kryazhimskii A.V., Maksimov V.I. and Osipov Yu.S. (1997): Reconstruction of extremal perturbations in parabolic equations. - Comp. Math. Math. Phys., Vol.37, No.3, pp.288-298.
- Maksimov V.I. (1994): Control reconstruction for nonlinear parabolic equations. - IIASA Working Paper WP-94-04, IIASA, Laxenburg, Austria.
- Maksimov V. and Pandolfi L. (1999): Dynamical reconstruction of inputs for contraction semigroup systems: the boundary inputcase. - J. Optim. Theory Applic., Vol.103, No.2, pp.401-420. Zbl0956.49020
- Osipov Yu.S. and Kryazhimskii A.V. (1995): Inverse Problems for Ordinary Differential Equations: Dynamical Solutions. - London: Gordon and Breach. Zbl0884.34015
- Unbehauen H. (1990): Continuous time approaches to system identification. - Automatica, Vol.26, No.6, pp.23-35. Zbl0714.93007

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