Use of ANN in a research reactor power fuzzy controller

Abstract

Six artificial neural networks (ANN) were developed to compute the membership values of the consequents of a fuzzy rule evaluation table, which is part of a Mamdani type fuzzy controller. This controller is aimed to regulate the neutron power of a research nuclear reactor. The neural networks obtained were validated over a wide range of input data. These ANN offer the possibility of a parallel processing of the fuzzy inputs, thus reducing the response time of the controller. © Springer-Verlag Berlin Heidelberg 2005.