Adaptive control over non­linear objects using the robust neural network FCMAC

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.128270

Keywords:

artificial neural network, fuzzy-СМАС, identification, modeling, indirect adaptive control, hashing

Abstract

The paper explores issues related to the application of artificial neural networks (ANN) when solving the problems on identification and control of nonlinear dynamic systems. We have investigated characteristics of the network, which is a result of the application of the apparatus of fuzzy logic in a classical СМАС neural network, which is titled FCMAC ‒ Fuzzy Cerebral Model Arithmetic Computer. We studied influence of the form of receptive fields of associative neurons on the accuracy of identification and control; various information hashing algorithms that make it possible to reduce the amount of memory required for the implementation of a network; robust learning algorithms are proposed allowing the use of a network in systems with strong perturbations. It is shown that the FСМАС network, when selecting appropriate membership functions, can be applied in order to synthesize indirect control systems with and without a reference model; it is more efficient to use it in control systems with the reference model. This sharply reduces the quantity of training pairs and simplifies the coding due to the narrower range of the applied values of input signals. The results obtained are confirmed by simulation modeling of the processes of identification of and control over nonlinear dynamical systems

Author Biographies

Oleg Rudenko, Simon Kuznets Kharkiv National University of Economics Nauky ave., 9-A, Kharkiv, Ukraine, 61166

Doctor of Technical Sciences, Professor, Head of Department

Department of information systems

Oleksandr Bezsonov, Simon Kuznets Kharkiv National University of Economics Nauky ave., 9-A, Kharkiv, Ukraine, 61166

Doctor of Technical Sciences, Professor

Department of information systems

Oleh Lebediev, Kharkiv National University of Radio Electronics Nauka аve., 14, Kharkiv, Ukraine, 61166

PhD, Associate Professor

Department of electronic computers

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Published

2018-04-10

How to Cite

Rudenko, O., Bezsonov, O., & Lebediev, O. (2018). Adaptive control over non­linear objects using the robust neural network FCMAC. Eastern-European Journal of Enterprise Technologies, 2(4 (92), 4–14. https://doi.org/10.15587/1729-4061.2018.128270

Issue

Vol. 2 No. 4 (92) (2018): Mathematics and Cybernetics - applied aspects

Section

Mathematics and Cybernetics - applied aspects

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Copyright (c) 2018 Oleg Rudenko, Oleksandr Bezsonov, Oleh Lebediev

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