Paper:
Language: English:

Some Applications of Soft Computing Methods in System Modeling and Control

Bela Lantos

Department of Control Engineering and Information Technology Technical University of Budapest, H-1111 Budapest, Muegyetem rkp. 9, Hungary

Received: October 10, 1997

Accepted: January 25, 1998

Keywords: Soft computing, Optimal controller parameter design, Neural robot control, Adaptive fazzy MIMO control

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.2, No.3 pp. 82-87, 1998

Abstract

The paper deals with the application of fuzzy systems, artificial neural networks (neural systems), and genetic algorithms to solve modeling and control problems in system engineering. Part 1 the paper covers the design of classical PID and fuzzy PID controllers for nonlinear systems with an (approximately) known dynamic model. Optimal controllers are designed based on genetic algorithms. Part 2 considers neural control of a SCARA robot. Part 3 deals with the fuzzy control of a special class of MIMO nonlinear systems and generalizes the method of Wang for such systems.

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