Using iterative learning algorithm and ANFIS training to compare type-1, type-2, fuzzy controller

Abstract

Iterative self-learning algorithm and ANFIS Training are two powerful tools for building the rule base of a fuzzy logic controller (FLC). Iterative learning algorithm is an effective control methodology, so it used to gather useful and trustful control Data and ANFIS is used to preprocess data and to extract fuzzy control rules from numerical data automatically as well as tune optimal membership functions of fuzzy system. We introduce a type-2 fuzzy logic system which can handle rule uncertainties. The presented is comparative between fuzzy type -1 and fuzzy type - 2 for the same problem. We use Matlab environment to run all simulations.