Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chu, SY | en_US |
dc.contributor.author | Teng, CC | en_US |
dc.date.accessioned | 2014-12-08T15:47:10Z | - |
dc.date.available | 2014-12-08T15:47:10Z | - |
dc.date.issued | 1999-01-01 | en_US |
dc.identifier.issn | 0165-0114 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/31646 | - |
dc.description.abstract | We propose a new PID tuning method using fuzzy neural networks for a given gain and phase margin specifications (FNGP). We use fuzzy neural networks to determine the PID controller parameters. Because the definitions of gain and phase margin equations are complex, an analytical tuning method for achieving specified gain and phase margins is not available yet. In this paper, a fuzzy neural modeling method is first proposed to identify the relationship between the gain-phase margin specifications and the PID controller parameters. Then, the FNGP is used to automatically tune the PID controllers parameter for different gain and phase margin specifications so that neither numerical methods nor graphical methods need be used Simulation results show that the FNGP can achieve the specified Values much more efficiently than other methods. (C) 1999 Elsevier Science B.V. All rights reserved. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | fuzzy neural network | en_US |
dc.subject | process control | en_US |
dc.subject | PID tuning | en_US |
dc.subject | gain and phase margin | en_US |
dc.title | Tuning of PID controllers based on gain and phase margin specifications using fuzzy neural network | en_US |
dc.type | Article | en_US |
dc.identifier.journal | FUZZY SETS AND SYSTEMS | en_US |
dc.citation.volume | 101 | en_US |
dc.citation.issue | 1 | en_US |
dc.citation.spage | 21 | en_US |
dc.citation.epage | 30 | en_US |
dc.contributor.department | 電控工程研究所 | zh_TW |
dc.contributor.department | Institute of Electrical and Control Engineering | en_US |
Appears in Collections: | Articles |
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