A Genetic-Based Fuzzy Clustering Algorithm for Fault Diagnosis in Satellite Attitude Determination System

Author

Lin, Cai ; Yuancan, Huang ; Jiabin, Chen

Author_Institution

Inf. Sci. & Technol. Sch., Beijing Inst. of Technol.

Volume

1

fYear

2006

fDate

16-18 Oct. 2006

Firstpage

834

Lastpage

837

Abstract

The paper presents a genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system (ADS). The traditional fuzzy c-means(FCM) algorithm is local search techniques that search for the optimum by using a hill-climbing techniques. Thus, it often fail in the search for global optimum. Genetic algorithm is a stochastic global optimization algorithm, their combination can prevent FCM being trapped in a local optimum and sensitive to the initializations. Simulation results show that the proposed approach have much higher probabilities of finding global optimal solutions than traditional FCM algorithm, and provide accurate clustering for fault mode

Keywords

fault diagnosis; fuzzy set theory; genetic algorithms; pattern clustering; satellite communication; fault diagnosis; fuzzy c-means; fuzzy clustering; genetic algorithm; local search; satellite attitude determination system; stochastic global optimization algorithm; Clustering algorithms; Fault diagnosis; Fuzzy sets; Fuzzy systems; Genetic algorithms; Intelligent sensors; Paper technology; Position measurement; Satellites; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on

Conference_Location

Jinan

Print_ISBN

0-7695-2528-8

Type

conf

DOI

10.1109/ISDA.2006.57

Filename

4021547