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Vol.11, No.2, May 2022. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS 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.
Abstract:
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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