Vol.11, No.2, May 2022.                                                                                                                                                                                   ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Artificial Neural Network-based Neurocontroller for Hydropower Plant Control


Radmila Koleva, Ana M. Lazarevska, Darko Babunski


© 2022 Radmila Koleva, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 11, Issue 2, Pages 506-512, ISSN 2217-8309, DOI: 10.18421/TEM112-02, May 2022.


Received: 09 February 2022.

Revised:   29 March 2022.
Accepted: 05 April 2022.
Published: 27 May 2022.




In this paper, the behavior of a system dynamics is represented where neuro-controller is designed, trained, and implemented. The development of the mathematical models is based on suggestions and recommendations from the literature issued by the working group of IEEE. According to the mathematical models, simulation is developed in Simulink software. MATLAB/Simulink software was used to represent the difference between the conventional PID controller and artificial neural network (ANN) neuro-controller. Nonlinear autoregressive-moving average (NARMA-L2) has been used for control simulation of the hydro-power plant (HPP) with neuro-controllers on one hand, and conventional PID control on the other hand.


Keywords –neuro-controller, PID controller, HPP control.



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