Title :
FD on Systems Type 1 and 2 Using Conditional Observers
Author :
Garcia, R.F. ; Castelo, J.P. ; Pazos, A.P. ; Rolle, J.L.C.
Author_Institution :
Univ. da Coruna, A Coruna
Abstract :
Most of non-linear type 1 and type 2 control systems suffers from lack of detectability when model based techniques are applied on FDI tasks. This research work presents an strategy based on conditional observers implemented by means of massive neural networks based models applied on a parity space approach. Conditional observers are modeled using a novel neural network based approach. As consequence of such technique on nonlinear plants of types one and two, useful results were achieved.
Keywords :
fault diagnosis; neural nets; observers; FDI task; conditional observers; fault detection; massive neural networks based model; nonlinear type 1 systems control systems; nonlinear type 2 systems control systems; parity space approach; Actuators; Backpropagation; Equations; Fault detection; Filters; Neural networks; Observers; Parameter estimation; Redundancy; Sequential analysis; Backpropagation; Conditional observer; Conjugate gradient; Fault detection; Fault isolation; Neural Networks;
Conference_Titel :
Automation Congress, 2006. WAC '06. World
Conference_Location :
Budapest
Print_ISBN :
1-889335-33-9
DOI :
10.1109/WAC.2006.376017
