ANFIS based modelling and control of non-linear systems: a tutorial
| Autor: | F. Palis, Mouloud Denai, Abdelhafid Zeghbib |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Soft computing
Adaptive neuro fuzzy inference system Artificial neural network Computer science business.industry Evolutionary algorithm Inference Fuzzy control system Nonlinear control Machine learning computer.software_genre Fuzzy logic Evolutionary computation Nonlinear system Adaptive system Genetic algorithm Artificial intelligence Intelligent control business computer |
| Zdroj: | SMC (4) |
| Popis: | This work is an attempt to illustrate the utility and effectiveness of soft-computing approaches in handling the modelling and control of complex systems. Soft computing research is concerned with the integration of artificial intelligent tools (neural networks, fuzzy technology, and evolutionary algorithms) in a complementary hybrid framework for solving real world problems. The present work concentrates on the pioneering neuro-fuzzy system ANFIS (adaptive neuro fuzzy inference system). ANFIS is first used to model nonlinear knee-joint dynamics from recorded clinical data. The established model is then used to predict the behaviour of the underlying system and for the design and evaluation of various intelligent control strategies. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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