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Automatic Loop-Shaping of QFT Controllers Using GAs and Evolutionary Computation

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AI 2005: Advances in Artificial Intelligence (AI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3809))

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Abstract

This paper presents a design method of the automatic loop-shaping which couples up manual loop-shaping method to genetic algorithms (GAs) in quantitative feedback theory (QFT). The loop-shaping is currently performed in computer aided design environments manually, and moreover, it is usually a trial and error procedure. To solve this problem, an automatic loop-shaping method based on GAs and evolutionary computation is developed and a benchmark example is used to examine the performance of the proposed automatic loop-shaping compared with that of the manual loop-shaping and similar other research.

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References

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Author information

Authors and Affiliations

  1. Sejong-Lockheed Martin Aerospace Research Center, Sejong University, 98 Kunja, Kwangjin, Seoul, 143-747, Korea

    Min-Soo Kim

  2. Electrical Engineering Department, Soongsil University, 1-1 Sangdo, Dongjak, Seoul, 156-743, Korea

    Chan-Soo Chung

Authors
  1. Min-Soo Kim
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  2. Chan-Soo Chung
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Editor information

Editors and Affiliations

  1. Guangxi Normal University, College of CS and IT, Guilin, China, and University of Technology, Faculty of Engineering and Information Technology, Sydney, Australia

    Shichao Zhang

  2. Department of Electrical and Computer Systems Engineering, Monash University, 3800, Melbourne, Victoria, Australia

    Ray Jarvis

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© 2005 Springer-Verlag Berlin Heidelberg

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Kim, MS., Chung, CS. (2005). Automatic Loop-Shaping of QFT Controllers Using GAs and Evolutionary Computation. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_147

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  • DOI: https://doi.org/10.1007/11589990_147

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30462-3

  • Online ISBN: 978-3-540-31652-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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