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.

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Title Hybrid controller with the combination of FLC and neural network-based IMC for nonlinear processes
Author(s) Hosen, Mohammad AnwarORCID iD for Hosen, Mohammad Anwar orcid.org/0000-0001-8282-3198
Salaken, Syed Moshfeq
Khosravi, AbbasORCID iD for Khosravi, Abbas orcid.org/0000-0001-6927-0744
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Creighton, DouglasORCID iD for 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
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