- Tytuł:
- Parameter Estimation Based Fault Detection and Isolation in Wiener and Hammerstein Systems
- Autorzy:
- Janczak, A.
- Powiązania:
- https://bibliotekanauki.pl/articles/908281.pdf
- Data publikacji:
- 1999
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
wykrywanie błędu
wyodrębnienie błędu
estymacja parametryczna
sieć neuronowa
system nieliniowy
fault detection
fault isolation
parameter estimation
neural networks
nonlinear system - Opis:
- 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.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 1999, 9, 3; 711-735
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki