Fusion of fuzzy, NN, GA to the intelligent robotics

Abstract

Recently, fuzzy system is used in many fields and places. In order to apply the system to various fields, the tuning and optimizing method of the fuzzy system is the key issue. Some self-tuning methods have been proposed so far. However, these conventional self-tuning methods do not have sufficient capability of learning. In this paper, we propose a new unsupervised/supervised self-tuning fuzzy system, which consists of some membership function expressed by the radial basis function with insensitive region. Teaming is carried out by the genetic algorithms. The descent method is also utilized for tuning the shapes of membership function and consequent parts in the case of supervised learning. The effectiveness of the proposed methods is shown by some numerical examples and simulations.