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Fuzzy control based on reinforcement learning for voice coil motor

dc.citation.epage269en_US
dc.citation.spage264en_US
dc.contributor.authorLiu, T. S.en_US
dc.contributor.authorChang, W. K.en_US
dc.contributor.department機械工程學系zh_TW
dc.contributor.departmentDepartment of Mechanical Engineeringen_US
dc.date.accessioned2014-12-08T15:25:35Z
dc.date.available2014-12-08T15:25:35Z
dc.date.issued2005en_US
dc.description.abstractDealing with voice coil motors, this paper presents reinforcement learning based fuzzy control, which incorporates characteristics of reinforcement learning into fuzzy control. Fuzzy control has excellent characteristics of dealing with model uncertainty and nonlinearity. To complement and improve fuzzy control, reinforcement learning is used to process rough feedback signals. This work constructs fuzzy rules based model based on input-output data of plants and tune fuzzy membership functions by reinforcement learning.en_US
dc.identifier.isbn1-4244-0020-1en_US
dc.identifier.journal2005 ICSC Congress on Computational Intelligence Methods and Applications (CIMA 2005)en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/17987
dc.identifier.wosnumberWOS:000239918800051
dc.language.isoen_USen_US
dc.titleFuzzy control based on reinforcement learning for voice coil motoren_US
dc.typeProceedings Paperen_US

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