A Robust Actuator Gain Fault Detection and Isolation Scheme.

Autor: Talebi, Heidar A., Abdollahi, Farzaneh, Patel, Rajni V., Khorasani, Khashayar
Zdroj: Neural Network-based State Estimation of Nonlinear Systems; 2010, p83-98, 16p
Abstrakt: In this chapter, a robust fault detection and isolation strategy is presented for actuator gain fault in nonlinear systems. Unlike the FDI scheme introduced in Chapter 4 and many other methods currently exist in the literature, the proposed FDI scheme in this chapter does not rely on the availability of all state measurements.Moreover, the learning rule employed for neural network observer is based on a modified dynamic backpropagation methodology as opposed to static backpropagation which makes the stability analysis of the overall system much more challenging. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index