Authors:
Theodore L. Kottas
1
;
Yiannis S. Boutalis
1
and
Manolis A. Christodoulou
2
Affiliations:
1
Democritus University of Thrace, Greece
;
2
Technical University of Crete, Greece
Keyword(s):
Fuzzy Cognitive Maps, Hebbian rule, State feedback, Weight Updating.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Decision Support Systems
;
Fuzzy Control
;
Fuzzy Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Machine Learning in Control Applications
;
Soft Computing
Abstract:
Fuzzy Cognitive Maps (FCMs) have found many applications in social -financial -political problems. In this paper we propose a method of FCM operation, which can be used to represent and control any real system, including traditional electro-mechanical systems. In the proposed approach the FCM reaches its equilibrium point using direct feedback from the node values of the real system and the limitations imposed by the control objectives for the node values of the system. The experts’ knowledge, which is represented in the weights of the nodes’ interconnections, undergoes a continuous on-line adaptation based on feedback from the real system. An algorithm for weight updating is proposed, which is based on system feedback and which includes specially designed matrices that lead the FCM and consequently the real system associated with it in a balanced equilibrium state. The proposed methodology is tested by simulating the operation of a hydro-electric plant.