Hybrid controller with the combination of FLC and neural network-based IMC for nonlinear processes Hosen, Mohammad Anwar, Salaken, Syed Moshfeq, Khosravi, Abbas, Nahavandi, Saeid and Creighton, Douglas 2015, Hybrid controller with the combination of FLC and neural network-based IMC for nonlinear processes, in ICONIP 2015 : Neural information processing : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015 : proceedings, Springer, Berlin, Germany, pp. 1-10, doi: 10.1007/978-3-319-26555-1_24. Attached Files Name Description MIMEType Size Downloads Title Hybrid controller with the combination of FLC and neural network-based IMC for nonlinear processes Author(s) Hosen, Mohammad Anwar orcid.org/0000-0001-8282-3198 Salaken, Syed Moshfeq Khosravi, Abbas orcid.org/0000-0001-6927-0744 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Creighton, Douglas orcid.org/0000-0002-9217-1231 Conference name Neural Information Processing. Conference (22nd : 2015 : Istanbul, Turkey) Conference location Istanbul, Turkey Conference dates 9-12 Nov. 2015 Title of proceedings ICONIP 2015 : Neural information processing : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015 : proceedings Editor(s) Arik, Sabri Huang, Tingwen Lin, Weng Kin Liu, Qingshan Publication date 2015 Start page 1 End page 10 Total pages 10 Publisher Springer Place of publication Berlin, Germany Keyword(s) Fuzzy logic controller Hybrid controller Internal model- based controller Neural network Forward model Inverse model Summary This 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. ISBN 9783319265544 ISSN 0302-9743 1611-3349 Language eng DOI 10.1007/978-3-319-26555-1_24 Field of Research 090407 Process Control and Simulation 08 Information And Computing Sciences Socio Economic Objective 970109 Expanding Knowledge in Engineering HERDC Research category E1 Full written paper - refereed ERA Research output type E Conference publication Copyright notice ©2015, Springer Persistent URL http://hdl.handle.net/10536/DRO/DU:30082481 Document type: Conference Paper Collection: Centre for Intelligent Systems Research Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 31 Mar 2016, 08:06:53 EST Thu, 31 Mar 2016, 08:16:54 EST Thu, 31 Mar 2016, 08:17:26 EST Thu, 31 Mar 2016, 08:31:04 EST Fri, 01 Apr 2016, 04:00:10 EST Fri, 01 Apr 2016, 05:07:53 EST Wed, 27 Apr 2016, 11:41:44 EST Wed, 27 Apr 2016, 11:45:10 EST Mon, 18 Jul 2016, 16:04:04 EST Thu, 08 Feb 2018, 09:58:07 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 268 Abstract Views, 4 File Downloads  -  Detailed Statistics Created: Thu, 31 Mar 2016, 08:31:04 EST

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