Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/62166
Full metadata record
DC FieldValueLanguage
dc.contributor.authorC. Treesatayapunen_US
dc.date.accessioned2018-09-11T09:22:58Z-
dc.date.available2018-09-11T09:22:58Z-
dc.date.issued2005-01-01en_US
dc.identifier.issn1569190Xen_US
dc.identifier.other2-s2.0-12444288509en_US
dc.identifier.other10.1016/j.simpat.2004.09.003en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=12444288509&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/62166-
dc.description.abstractIn this paper, a direct adaptive control for drug infusion of biological systems is presented. The proposed controller is accomplished using our adaptive network called Fuzzy Rules Emulated Network (FREN). The structure of FREN resembles the human knowledge in the form of fuzzy If-Then rules. After selecting the initial value of network's parameters, an on-line adaptive process based on Lyapunov's criteria is performed to improve the controller performance. The control signal from FREN is designed to keep in the stable region which is calculated by the modified sliding mode control (SMC). The simulation results indicate that the proposed algorithm can satisfy the setting point and the robust performance. © 2004 Elsevier B.V. All rights reserved.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleControl of drug infusion for biological systems using FREN with sliding boundsen_US
dc.typeJournalen_US
article.title.sourcetitleSimulation Modelling Practice and Theoryen_US
article.volume13en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.