1. University of Anbar
  2. الكليات
  3. كلية الهندسة
  4. الهندسة الكهربائية
Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3668
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dc.contributor.authorYousif Al Mashhadany-
dc.date.accessioned2022-10-20T05:41:34Z-
dc.date.available2022-10-20T05:41:34Z-
dc.date.issued2012-
dc.identifier.issn2212-6716-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/3668-
dc.description.abstractThe proposed controller incorporates fuzzy logic (FL) algorithm with artificial neural network (ANN). ANFIS replaces the conventional PI controller, tuning the fuzzy inference system with a hybrid learning algorithm. A tuning method is proposed for training of the neuro-fuzzy controller. The best rule base and the best training algorithm chosen produced high performance in the ANFIS controller. Simulation was done on MATLAB Ver. 2010a. A case study was Chopper-Fed DC Motor Drive, in continuous and discrete modes. Satisfactory results show the ANFIS controller able to control dynamic highly-nonlinear systems. Tuning it further improved the results.en_US
dc.language.isoenen_US
dc.publisherAASRI Procedia Journal ( https://www.sciencedirect.com/journal/aasri-procedia )en_US
dc.subjectAdaptive Neuro-Fuzzy Inference Systemen_US
dc.subjectChopper-fed DC-motor driveen_US
dc.subjectNeuro Fuzzy controlleren_US
dc.titleHigh-Performance ANFIS Controlleren_US
dc.typeArticleen_US
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