DocumentCode :
2795974
Title :
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
Link To Document :
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