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

Year 2019, , 121 - 136, 30.12.2019

Mehmet Serhat Can , Murat Sam

https://doi.org/10.36222/ejt.650617

Abstract

Fuzzy Logic Controllers (FLCs) are
effective solutions for nonlinear and parameter variability systems, but it
contains multiple mathematical operations causing the controller to react
slowly. This study aims to obtain a controller that can imitate the effective
control performance of the FLC, which is easy to design both in software and
hardware, and has a short response time. Artificial neural networks (ANNs)
provide effective solutions in system modeling. Modeling of FLC has been
realized by using of ANN’s learning and parallel processing capability. The
design process of the FLC and the training processes of the ANN were studied in
Matlab SIMULINK environment. In the study, FLC was modelled at high similarity
ratio with small ANN structure. ANN results were obtained very faster than the
FLC control performance. The control performances of two controllers were
observed to be very close to each other. As a result, ANN model has smaller
structure than FLC, which makes it possible to implement the controller easily
in terms of hardware and software.

Keywords

Fuzzy logic controller, artificial neural network

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