A neural network-based fault detection scheme for satellite Attitude Control Systems

被引：0

作者：

Talebi, HA ^{[1
]}

Patel, RV ^{[1
]}

机构：

[1] Amirkabir Univ Technol, Fac Elect Engn, Tehran, Iran

来源：

2005 IEEE INTERNATIONAL CONFERENCE ON CONTROL APPLICATIONS (CCA), VOLS 1AND 2 | 2005年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents an actuator Fault Detection and Identification (FDI) scheme for satellite attitude control systems. A state-space approach is used and a nonlinear-inparameters neural network (NLPNN) is employed to identify the general unknown fault. The recurrent network configuration is obtained by a combination of feedforward network architectures and dynamical elements in the form of stable filters. The neural network weights are updated based on a modified backpropagation scheme. The stability of the overall fault detection scheme is shown using Lyapunov's direct method. Simulation results are presented to show the performance of the proposed fault detection scheme.

引用

页码：1293 / 1298

页数：6

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