Modeling and control of non-linear systems using soft computing techniques

Authors:
M. A. Denaï;F. Palis;A. Zeghbib
Affiliations:
Faculty of Electrical Engineering, USTO, BP 1505 El-Mnaouar, Oran 31000, Algeria;Institut für Elektrische Energiesysteme, Universität Magdeburg, Postfach 4120, 39016 Magdeburg, Germany;Institut für Elektrische Energiesysteme, Universität Magdeburg, Postfach 4120, 39016 Magdeburg, Germany
Venue:
Applied Soft Computing
Year:
2007

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Abstract

This work is an attempt to illustrate the utility and effectiveness of soft computing approaches in handling the modeling and control of complex systems. Soft computing research is concerned with the integration of artificial intelligent tools (neural networks, fuzzy technology, evolutionary algorithms, ...) in a complementary hybrid framework for solving real world problems. There are several approaches to integrate neural networks and fuzzy logic to form a neuro-fuzzy system. The present work will concentrate on the pioneering neuro-fuzzy system, Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is first used to model non-linear knee-joint dynamics from recorded clinical data. The established model is then used to predict the behavior of the underlying system and for the design and evaluation of various intelligent control strategies.