IMITATION OF FUZZY LOGIC CONTROLLER BASED ARTIFICIAL NEURAL NETWORK, AND APPLICATION OF INVERTED PENDULUM SYSTEM CONTROL

Abstract

Fuzzy Logic Controllers (FLCs) are effective solutions for nonlinear andparameter variability systems, but it contains multiple mathematicaloperations causing the controller to react slowly. This study aims to obtain acontroller that can imitate the effective control performance of the FLC,which is easy to design both in software and hardware, and has a shortresponse time. Artificial neural networks (ANNs) provide effective solutionsin system modeling. Modeling of FLC has been realized by using of ANN’slearning and parallel processing capability. The design process of the FLCand the training processes of the ANN were studied in Matlab SIMULINKenvironment. In the study, FLC was modelled at high similarity ratio withsmall ANN structure. ANN results were obtained very faster than the FLCcontrol performance. The control performances of two controllers wereobserved to be very close to each other. As a result, ANN model has smallerstructure than FLC, which makes it possible to implement the controllereasily in terms of hardware and software.