Detecting faults in a hydraulic system using neural network and observer approaches.

• Autorzy: Shields D.N. , Du S. , Gaura E.
• Języki publikacji: EN

Abstrakty

EN

A robust fault detection observer (RFDO), which includes a robust residual, is designed for a general nonlinear system with polynomial-type nonlinearities. Two main theoretical results are given for the existence, stability and the detectability of the RFDO. The approach is applied to a three-tank hydraulic system where two fault scenarios are considered. Three different degree observers, with corresponding residuals, are assessed. This observer approach is then compared to the performance of a neural network approach under the same fault conditions.

Słowa kluczowe

EN

robust fault detection observer; nonlinear systems; polynomial-type nonlinearities; stability; detectability; three-tank hydraulic system; neural network; continuous-time system

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Systems Science
• Rocznik: 2002
• Tom: Vol. 28, nr 1
• Strony: 85--106
• Opis fizyczny: Bibliogr. 27 poz.

Twórcy

autor

Shields D.N.

• Maths-MIS, Voventry University, Priory St, Voventry, CV15FB, U.K.

autor

Du S.

• Maths-MIS, Voventry University, Priory St, Voventry, CV15FB, U.K.

autor

Gaura E.

• Maths-MIS, Voventry University, Priory St, Voventry, CV15FB, U.K.