ANFIS Controller and Its Application

ANFIS Controller and Its Application
Authors : Akhil V. Gite, Raksha M. Bodade, Bhagyashri M. Raut
Publication Date: 28-02-2013


Author(s):   Akhil V. Gite, Raksha M. Bodade, Bhagyashri M. Raut

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Vol.2 - Issue 2 (February - 2013)

e-ISSN:   2278-0181


The concept of fuzzy logic and artificial neural network for control problem has been grown into a popular research topic in recent years. The reason is that the classical control theory usually requires a mathematical model for designing the controller. The inaccuracy of mathematical modeling of the plants usually degrades the performance of the controller, especially for nonlinear and complex control problems. The advent of the fuzzy logic controllers (FLC) and the neural controllers based on multilayered neural networks has inspired new resources for the possible realization of better and more efficient control. In recent years, the integration between fuzzy logic and neural network namely fuzzy neural network (FNN) has been proposed and developed; generally the combination of fuzzy logic and neural network is called as ANFIS (Adaptive Neuro Fuzzy Inference System). Neural system has many input and also has multiple outputs but the fuzzy logic has multiple inputs and single output, so the combination of this two is know as ANFIS which is used for nonlinear applications.[1]


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