Brain emotional learning based intelligent controller applied to neurofuzzy model of micro-heat exchanger

In this paper, an intelligent controller is applied to govern the dynamics of electrically heated micro-heat exchanger plant. First, the dynamics of the micro-heat exchanger, which acts as a nonlinear plant, is identified using a neurofuzzy network. To build the neurofuzzy model, a locally linear le...

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Bibliographic Details
Published in:Expert systems with applications 2007-04, Vol.32 (3), p.911-918
Main Authors: Rouhani, Hossein, Jalili, Mahdi, Araabi, Babak N., Eppler, Wolfgang, Lucas, Caro
Format: Article
Language:English
Subjects:
Emotion based learning
Heat exchanger
Intelligent control
Locally linear models
Neurofuzzy models
Nonlinear system identification
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Summary:In this paper, an intelligent controller is applied to govern the dynamics of electrically heated micro-heat exchanger plant. First, the dynamics of the micro-heat exchanger, which acts as a nonlinear plant, is identified using a neurofuzzy network. To build the neurofuzzy model, a locally linear learning algorithm, namely, locally linear mode tree (LoLiMoT) is used. Then, an intelligent controller based on brain emotional learning algorithm is applied to the identified model. The intelligent controller is based on a computational model of limbic system in the mammalian brain. The brain emotional learning based intelligent controller (BELBIC) based on PID control is adopted for the micro-heat exchanger plant. The contribution of BELBIC in improving the control system performance is shown by comparison with results obtained from classic PID controller without BELBIC. The results demonstrate excellent improvements of control action, without any considerable increase in control effort for PID + BELBIC.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2006.01.047