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http://elar.urfu.ru/handle/10995/118113
Название: | A Proposed ANN-Based Acceleration Control Scheme for Soft Starting Induction Motor |
Авторы: | Menaem, A. A. Elgamal, M. Abdel-Aty, A. -H. Mahmoud, E. E. Chen, Z. Hassan, M. A. |
Дата публикации: | 2021 |
Издатель: | Institute of Electrical and Electronics Engineers Inc. |
Библиографическое описание: | A Proposed ANN-Based Acceleration Control Scheme for Soft Starting Induction Motor / A. A. Menaem, M. Elgamal, A. -H. Abdel-Aty et al. // IEEE Access. — 2021. — Vol. 9. — P. 4253-4265. |
Аннотация: | In this article, a new soft starting control scheme based on an artificial neural network (ANN) is presented for a three-phase induction motor (IM) drive system. The main task of the control scheme is to keep the accelerating torque constant at a level based on the value of reference acceleration. This is accomplished by the proper choice of the firing angles of thyristors in the soft starter. Using the ANN approach, the complexity of the online determination of the thyristors firing angles is resolved. The IM torque-speed characteristic curves are firstly used to train the ANN model. Secondly, the IM- soft starter system is modeled using MATLAB/SIMULINK. To prove the effectiveness of the proposed ANN-based acceleration control scheme, different reference accelerations and loading conditions are applied and investigated. Finally, a laboratory prototype of 3 kW soft starter is implemented. The proposed control scheme is executed in a real-time environment using a digital signal processor (Model: TMS320F28335). The simulation and real-time results significantly confirm that the proposed controller can efficiently reduce the IM starting current and torque pulsations. This in turn ensures a smooth acceleration of the IM during the starting process. Moreover, the proposed control scheme has the superiority over several soft starting control schemes since it has a simple control circuit configuration, less required sensors, and low computational burden of the control algorithm. © 2021 Institute of Electrical and Electronics Engineers Inc.. All rights reserved. |
Ключевые слова: | ACCELERATION CONTROL ARTIFICIAL NEURAL NETWORK DIGITAL SIGNAL PROCESSING INDUCTION MOTORS ACCELERATION ACCELERATION CONTROL DIGITAL SIGNAL PROCESSORS IGNITION INDUCTION MOTORS MATLAB NEURAL NETWORKS SIGNAL PROCESSING STARTERS THYRISTORS COMPUTATIONAL BURDEN CONTROL CIRCUITS LOADING CONDITION ON-LINE DETERMINATION REAL-TIME ENVIRONMENT THREE PHASE INDUCTION MOTOR TORQUE PULSATION TORQUE SPEED CHARACTERISTIC ELECTRIC MACHINE CONTROL |
URI: | http://elar.urfu.ru/handle/10995/118113 |
Условия доступа: | info:eu-repo/semantics/openAccess |
Идентификатор SCOPUS: | 85098748017 |
Идентификатор WOS: | 000607657000001 |
Идентификатор PURE: | 20520438 |
ISSN: | 21693536 |
DOI: | 10.1109/ACCESS.2020.3046848 |
Располагается в коллекциях: | Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC |
Файлы этого ресурса:
Файл | Описание | Размер | Формат | |
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2-s2.0-85098748017.pdf | 2,52 MB | Adobe PDF | Просмотреть/Открыть |
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