This paper develops an adaptive approximation based approach for distributed fault diagnosis for a class of interconnected continuous-time nonlinear systems with modeling uncertainties and measurement noise. The proposed approach integrates learning with filtering techniques and allows the derivation of tight detection thresholds. This is accomplished in two ways: at first by learning the modeling uncertainty through adaptive approximation methods, so that the learned function is used for the derivation of the residual signal, and then by using filtering for dampening measurement noise. The required signals for both tasks are derived through a two-stage filtering process, by exploiting the properties of the filtering framework. Finally, simulation results are used to demonstrate the effectiveness of the proposed approach

A Distributed Fault Diagnosis Approach Utilizing Adaptive Approximation for a Class of Interconnected Continuous-Time Nonlinear Systems

PARISINI, Thomas
2014

Abstract

This paper develops an adaptive approximation based approach for distributed fault diagnosis for a class of interconnected continuous-time nonlinear systems with modeling uncertainties and measurement noise. The proposed approach integrates learning with filtering techniques and allows the derivation of tight detection thresholds. This is accomplished in two ways: at first by learning the modeling uncertainty through adaptive approximation methods, so that the learned function is used for the derivation of the residual signal, and then by using filtering for dampening measurement noise. The required signals for both tasks are derived through a two-stage filtering process, by exploiting the properties of the filtering framework. Finally, simulation results are used to demonstrate the effectiveness of the proposed approach
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11368/2808540
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact