Full metadata record
DC FieldValueLanguage
dc.contributor.authorPerng, Jau-Woeien_US
dc.contributor.authorMa, Li-Shanen_US
dc.contributor.authorWu, Bing-Feien_US
dc.date.accessioned2014-12-08T15:06:49Z-
dc.date.available2014-12-08T15:06:49Z-
dc.date.issued2010-06-01en_US
dc.identifier.issn0941-0643en_US
dc.identifier.urihttp://dx.doi.org/10.1007/s00521-009-0319-2en_US
dc.identifier.urihttp://hdl.handle.net/11536/5350-
dc.description.abstractBased on some useful frequency domain methods, this paper proposes a systematic procedure to address the limit cycle prediction of a neural vehicle control system with adjustable parameters. A simple neurocontroller can be linearized by using describing function method firstly. According to the classical method of parameter plane, the stability of linearized system with adjustable parameters is then considered. In addition, gain margin and phase margin for limit cycle generation are also analyzed by adding a gain-phase margin tester into open loop system. Computer simulations show the efficiency of this approach.en_US
dc.language.isoen_USen_US
dc.subjectNeural networken_US
dc.subjectDescribing functionsen_US
dc.subjectGain-phase marginen_US
dc.subjectVehicleen_US
dc.titleLimit cycle prediction of a neurocontrol vehicle system based on gain-phase margin analysisen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s00521-009-0319-2en_US
dc.identifier.journalNEURAL COMPUTING & APPLICATIONSen_US
dc.citation.volume19en_US
dc.citation.issue4en_US
dc.citation.spage565en_US
dc.citation.epage571en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000277940600008-
dc.citation.woscount1-
Appears in Collections:Articles


Files in This Item:

  1. 000277940600008.pdf

If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.