Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김희준 | - |
dc.date.accessioned | 2022-06-07T05:44:05Z | - |
dc.date.available | 2022-06-07T05:44:05Z | - |
dc.date.issued | 1999-11 | - |
dc.identifier.citation | IECON'99. Conference Proceedings. 25th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.99CH37029) Industrial Electronics Society, 1999. IECON '99 Proceedings. The 25th Annual Conference of the IEEE. 2:625-629 vol.2 1999 | en_US |
dc.identifier.issn | 0-7803-5735-3 | - |
dc.identifier.issn | 978-0-7803-5735-8 | - |
dc.identifier.uri | https://ieeexplore.ieee.org/document/816464?arnumber=816464&SID=EBSCO:edseee | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/171301 | - |
dc.description.abstract | The fuzzy logic controller has been focused in the field of vector control of induction motors. However, a systematic method for designing and tuning the fuzzy logic controller is not developed yet. In this paper, an auto-tuning method for fuzzy logic controller based on the genetic algorithm is presented. In the proposed method, normalization parameters and membership function parameters of a fuzzy controller are translated into binary bit-strings, which are processed by the genetic algorithm in order to be optimized for the well-chosen objective function (i.e. fitness function). To examine the validity of the proposed method, a genetic algorithm based fuzzy controller for an indirect vector control of induction motors is simulated and an experiment is carried out. The simulation and experimental results show a significant enhancement in shortening development time and improving system performance over a traditional manually tuned fuzzy logic controller. Thus, in the case of changing motor, the proposed method is superior to a traditional method in the respect of development time and system performance. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.subject | Velocity control | en_US |
dc.subject | Induction motors | en_US |
dc.subject | Genetic algorithms | en_US |
dc.subject | Fuzzy logic | en_US |
dc.subject | Machine vector control | en_US |
dc.subject | Fuzzy control | en_US |
dc.subject | System performance | en_US |
dc.subject | Design methodology | en_US |
dc.subject | Control systems | en_US |
dc.subject | Optimization methods | en_US |
dc.title | Speed Control of Induction Motor Using Genetic Algorithm Based Fuzzy Controller | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/IECON.1999.816464 | - |
dc.relation.journal | 국제Proceeding(기타) | - |
dc.contributor.googleauthor | Oh, Won-Seok | - |
dc.contributor.googleauthor | Kim, Young-Tae | - |
dc.contributor.googleauthor | Kim, Chang-Sun | - |
dc.contributor.googleauthor | Kwon, Tae-Seok | - |
dc.contributor.googleauthor | Kim, Hee-Jun | - |
dc.relation.code | 2012101922 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF ENGINEERING SCIENCES[E] | - |
dc.sector.department | SCHOOL OF ELECTRICAL ENGINEERING | - |
dc.identifier.pid | hjkim | - |
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