A genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system

Lin Cai; Yuancan Huang; Jiabin Chen

doi:10.1109/ISDA.2006.57

A genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system

Lin Cai^*, Yuancan Huang, Jiabin Chen

^*Corresponding author for this work

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings - ISDA 2006
Subtitle of host publication	Sixth International Conference on Intelligent Systems Design and Applications
Pages	834-837
Number of pages	4
DOIs	https://doi.org/10.1109/ISDA.2006.57
Publication status	Published - 2006
Event	ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications - Jinan, China Duration: 16 Oct 2006 → 18 Oct 2006

Publication series

Name	Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications
Volume	1

Conference

Conference	ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications
Country/Territory	China
City	Jinan
Period	16/10/06 → 18/10/06

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10.1109/ISDA.2006.57

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Cai, L., Huang, Y., & Chen, J. (2006). A genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system. In Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications (pp. 834-837). Article 4021547 (Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications; Vol. 1). https://doi.org/10.1109/ISDA.2006.57

Cai, Lin ; Huang, Yuancan ; Chen, Jiabin. / A genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system. Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications. 2006. pp. 834-837 (Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications).

@inproceedings{b4e9f083c7f24e84a692f7a801f7d209,

title = "A genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system",

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.",

author = "Lin Cai and Yuancan Huang and Jiabin Chen",

year = "2006",

doi = "10.1109/ISDA.2006.57",

language = "English",

isbn = "0769525288",

series = "Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications",

pages = "834--837",

booktitle = "Proceedings - ISDA 2006",

note = "ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications ; Conference date: 16-10-2006 Through 18-10-2006",

}

Cai, L, Huang, Y & Chen, J 2006, A genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system. in Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications., 4021547, Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications, vol. 1, pp. 834-837, ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications, Jinan, China, 16/10/06. https://doi.org/10.1109/ISDA.2006.57

A genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system. / Cai, Lin; Huang, Yuancan ; Chen, Jiabin.
Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications. 2006. p. 834-837 4021547 (Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Huang, Yuancan

AU - Chen, Jiabin

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N2 - 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.

AB - 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.

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Cai L, Huang Y , Chen J. A genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system. In Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications. 2006. p. 834-837. 4021547. (Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications). doi: 10.1109/ISDA.2006.57

A genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system

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