GA-based fuzzy reinforcement learning for control of a magnetic bearing system
This paper proposes a TD (temporal difference) and GA (genetic algorithm)-based reinforcement (TDGAR) learning method and applies it to the control of a real magnetic bearing system. The TDGAR learning scheme is a new hybrid GA, which integrates the TD prediction method and the GA to perform the rei...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society. - 1996. - 30(2000), 2 vom: 15., Seite 276-89
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| 1. Verfasser: |
Lin, C T
(VerfasserIn) |
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| Weitere Verfasser: |
Jou, C P |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2000
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society
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| Schlagworte: | Journal Article |
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