Parameter Estimation Based Fault Detection and Isolation in Wiener and Hammerstein Systems

• Autorzy: Janczak A.
• Języki publikacji: EN

Abstrakty

EN

Fault detection and isolation in Wiener and Hammerstein systems via generation and processing of residual sequences is considered. We assume that some models of the unfaulty Wiener and Hammerstein systems under consideration are known. For Wiener systems, we also assume that their static nonlinear subsystems are invertible. Then, based on a serial-parallel definition of the residual error, new fault detection and isolation methods are proposed.To detect and identify all the changes in both the Wiener and Hammerstein system parameters, the sequences of residuals are processed by using linear regression methods or a neural network approach.

Słowa kluczowe

EN

fault detection; fault isolation; parameter estimation; neural networks; nonlinear system

PL

wykrywanie błędu; wyodrębnienie błędu; estymacja parametryczna; sieć neuronowa; system nieliniowy

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 1999
• Tom: Vol. 9, no 3
• Strony: 711--735
• Opis fizyczny: Bibliogr. 27 poz., rys., tab., wykr.

Twórcy

autor

Janczak A.

• Dept. of Robotics and Software Engineering Technical University of Zielona Gora ul. Podgorna 50, 65-246 Zielona Gora,Poland,