Issue |
E3S Web Conf.
Volume 563, 2024
International Conference on Environmental Science, Technology and Engineering (ICESTE 2024)
|
|
---|---|---|
Article Number | 02039 | |
Number of page(s) | 10 | |
Section | Civil Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202456302039 | |
Published online | 30 August 2024 |
Development a model of an adaptive fuzzy neural network controller for the control system of a synchronous motor with permanent magnet throttle bypass in the ammonia synthesis process
Navoi State Mining and Technology University, 200100 Navoi, Uzbekistan
* Corresponding author: azim_xj@mail.ru
In this work, we present an adaptive fuzzy controller utilizing a fuzzy neural network for the control system of a synchronous motor with permanent magnet throttle bypass in the ammonia synthesis process. This approach offers a straightforward design, eliminates the need for a system model, and removes the constraints of a fixed universal range for fuzzy output. By employing a fuzzy neural network, our method can dynamically identify and adjust to the control system, enabling effective adaptation without prior knowledge of the system's dynamics. Mathematical models and algorithms for the control system are developed, integrating motor dynamics with fuzzy logic and neural networks. Simulation and testing show the effectiveness of the proposed control system in regulating motor speed and torque. The study contributes to the advancement of motor control systems in industrial processes.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.