Classical model-based fault detection schemes for linear multivariable systems require the definition of suitable residual functions. This paper shows the possibility of identifying residual generators even when the system model is unknown, by following a black-box approach. The result is obtained by using canonical input-output polynomial forms which lead to characterise in a straightforward fashion the basis of the subspace described by all possible residual generators. The performance of the proposed identification method is tested by means of Monte Carlo simulations.

S. Simani, R. Diversi, U. Soverini (2005). Identification of residual generators for fault detection of linear dynamic models. s.l : IEEE Control Systems Society and EUCA.

Identification of residual generators for fault detection of linear dynamic models

DIVERSI, ROBERTO;SOVERINI, UMBERTO
2005

Abstract

Classical model-based fault detection schemes for linear multivariable systems require the definition of suitable residual functions. This paper shows the possibility of identifying residual generators even when the system model is unknown, by following a black-box approach. The result is obtained by using canonical input-output polynomial forms which lead to characterise in a straightforward fashion the basis of the subspace described by all possible residual generators. The performance of the proposed identification method is tested by means of Monte Carlo simulations.
2005
Proceedings of the 44th IEEE Conference on Decision and Control and European Control Conference ECC'05
7651
7655
S. Simani, R. Diversi, U. Soverini (2005). Identification of residual generators for fault detection of linear dynamic models. s.l : IEEE Control Systems Society and EUCA.
S. Simani; R. Diversi; U. Soverini
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/22322
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