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Calculation of PID controller parameters by using a fuzzy neural network

dc.citation.epage400en_US
dc.citation.issue3en_US
dc.citation.spage391en_US
dc.citation.volume42en_US
dc.citation.woscount9
dc.contributor.authorLee, CHen_US
dc.contributor.authorTeng, CCen_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.date.accessioned2014-12-08T15:40:39Z
dc.date.available2014-12-08T15:40:39Z
dc.date.issued2003-07-01en_US
dc.description.abstractIn this paper, we use the fuzzy neural network (FNN) to develop a formula for designing the proportional-integral-derivative (PID) controller. This PID controller satisfies the criteria of minimum integrated absolute error (IAE) and maximum of sensitivity (M-s). The FNN system is used to identify the relationship between plant model and controller parameters based, on IAE, and M-s. To derive the tuning rule, the dominant pole assignment method is a applied. to simplify our optimization processes. Therefore, the FNN system is used to automatically tune the PID controller for different system parameters so that neither theoretical methods not numerical methods need be used. Moreover; the FNN-based formula can modify the controller to meet our specification when the system model changes. A simulation result for applying to the motor position control problem is given to demonstrate the effectiveness of our approach. (C) 2003 ISA-The Instrumentation, Systems, and Automation Society.en_US
dc.identifier.issn0019-0578en_US
dc.identifier.journalISA TRANSACTIONSen_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/27727
dc.identifier.wosnumberWOS:000183931000005
dc.language.isoen_USen_US
dc.subjectPID controlleren_US
dc.subjectdominant pole assignmenten_US
dc.subjectfuzzy neural networken_US
dc.titleCalculation of PID controller parameters by using a fuzzy neural networken_US
dc.typeArticleen_US

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