Presentation 1995/6/30
Neurocontrol of Dynamic Systems Utilizing Unstable Characteristics (Control of Inverted Pendulum and Bicycle)
Kunihiko Nakazono, Hiroshi Kinjo, Shiro Tamaki, Tetsuhiko Yamamoto,
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Abstract(in English) Genetic algorithms (GAs) with rough evaluations can prompt the evolvement of neural networks that are able to control unstable dynamic systems. The proposed method makes full use of the merit of GAs that time-varying evaluations can be easily incorporated. First an easy evaluation in GAs induces the appearance of neural networks with controllability. Second, an evaluation of settling time prompts the evolvement of neural networks that show high performance. The method is applied to the control of an inverted pendulum and a bicycle.
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Keyword(in English) neural networks / direct control / genetic algorithms / inverted pendulum / bicycle / rough evaluation
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Committee NC
Conference Date 1995/6/30(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Neurocontrol of Dynamic Systems Utilizing Unstable Characteristics (Control of Inverted Pendulum and Bicycle)
Sub Title (in English)
Keyword(1) neural networks
Keyword(2) direct control
Keyword(3) genetic algorithms
Keyword(4) inverted pendulum
Keyword(5) bicycle
Keyword(6) rough evaluation
1st Author's Name Kunihiko Nakazono
1st Author's Affiliation Faculty of Engineering, University of the Ryukyus()
2nd Author's Name Hiroshi Kinjo
2nd Author's Affiliation Faculty of Engineering, University of the Ryukyus
3rd Author's Name Shiro Tamaki
3rd Author's Affiliation Faculty of Engineering, University of the Ryukyus
4th Author's Name Tetsuhiko Yamamoto
4th Author's Affiliation Faculty of Engineering, University of the Ryukyus
Date 1995/6/30
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Volume (vol) vol.95
Number (no) 135
Page pp.pp.-
#Pages 8
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