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Hybrid controller with the combination of FLC and neural network-based IMC for nonlinear processes
conference contribution
posted on 2015-01-01, 00:00 authored by Anwar HosenAnwar Hosen, Syed Moshfeq Salaken, Abbas KhosraviAbbas Khosravi, Saeid Nahavandi, Douglas CreightonDouglas CreightonThis work presents a hybrid controller based on the combination of fuzzy logic control (FLC) mechanism and internal model-based control (IMC). Neural network-based inverse and forward models are developed for IMC. After designing the FLC and IMC independently, they are combined in parallel to produce a single control signal. Mean averaging mechanism is used to combine the prediction of both controllers. Finally, performance of the proposed hybrid controller is studied for a nonlinear numerical plant model (NNPM). Simulation result shows the proposed hybrid controller outperforms both FLC and IMC.
History
Event
Neural Information Processing. Conference (22nd : 2015 : Istanbul, Turkey)Pagination
1 - 10Publisher
SpringerLocation
Istanbul, TurkeyPlace of publication
Berlin, GermanyPublisher DOI
Start date
2015-11-09End date
2015-11-12ISSN
0302-9743eISSN
1611-3349ISBN-13
9783319265544Language
engPublication classification
E Conference publication; E1 Full written paper - refereedCopyright notice
2015, SpringerEditor/Contributor(s)
S Arik, T Huang, W Lin, Q LiuTitle of proceedings
ICONIP 2015 : Neural information processing : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015 : proceedingsUsage metrics
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No categories selectedKeywords
Fuzzy logic controllerHybrid controllerInternal model- based controllerNeural networkForward modelInverse modelScience & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer Science, Theory & MethodsComputer ScienceInternal model-based controllerINTERVAL TYPE-2SYSTEMSCLASSIFICATIONAPPROXIMATIONREACTOR
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