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

  • Authors:
  • Hossein Rouhani;Mahdi Jalili;Babak N. Araabi;Wolfgang Eppler;Caro Lucas

  • Affiliations:
  • Mechanical Engineering Department, University of Tehran, Tehran, Iran;Control and Intelligent Processing Center of Excellence, Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran;Control and Intelligent Processing Center of Excellence, Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran;Institute of Data Processing and Electronics, Forschungszentrum Karlsruhe, Germany;Control and Intelligent Processing Center of Excellence, Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2007

Quantified Score

Hi-index 12.05

Visualization

Abstract

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.