Simultaneous optimization of topology of structural systrem and control system by genetic algorithms

Hiroshi Yamakawa, Yuji Takagi

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    An improved method of our previous simultaneous optimization method of structural and control systems is presented by utilizing the multilayered genetic algorithms under the special consideration on structural topology, parameters and collocations of control devices together with feedback gain parameters. In this study, we improve the previous method easy to consider both the numbers of sensors and actuators and their collocations. The improved method consists of three level optimizations by genetic algorithms. At the first step, topology optimization is held and then at the second step structural shape optimization, collocation and number optimizations of sensors and actuators are held in the first level and then optimum gains in the second level. Between the first and the second level informations are exchanged. Many numerical examples were obtained by the proposed method. The effectiveness of the proposed method was confirmed through those numerical examples.

    Original languageEnglish
    Title of host publication6th Symposium on Multidisciplinary Analysis and Optimization
    PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
    Pages1851-1856
    Number of pages6
    Publication statusPublished - 1996
    Event6th AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 1996 - Bellevue, United States
    Duration: 1996 Sep 41996 Sep 6

    Other

    Other6th AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 1996
    CountryUnited States
    CityBellevue
    Period96/9/496/9/6

    ASJC Scopus subject areas

    • Aerospace Engineering
    • Mechanical Engineering

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  • Cite this

    Yamakawa, H., & Takagi, Y. (1996). Simultaneous optimization of topology of structural systrem and control system by genetic algorithms. In 6th Symposium on Multidisciplinary Analysis and Optimization (pp. 1851-1856). American Institute of Aeronautics and Astronautics Inc, AIAA.