Structure identification of fuzzy model
Fuzzy Sets and Systems
Target tracking control of a mobile robot using a brain limbic system based control strategy
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A functional model of limbic system of brain
BI'09 Proceedings of the 2009 international conference on Brain informatics
Attention to multiple local critics in decision making and control
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
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.