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Hybrid AI for Enhanced Voltage Control in Three-Phase Boost Rectifiers | ||
| International Journal of Industrial Electronics Control and Optimization | ||
| مقاله 3، دوره 8، شماره 4، اسفند 2025، صفحه 363-374 اصل مقاله (865.61 K) | ||
| نوع مقاله: Research Articles | ||
| شناسه دیجیتال (DOI): 10.22111/ieco.2024.49558.1605 | ||
| نویسندگان | ||
| Alireza Khoshsoadat1؛ Arash Khoshooei2؛ Mohamad Abedini* 3؛ Mohammadreza Mirzaei4 | ||
| 1Department of Electrical Engineering, Shahid Beheshti University, Tehran, Iran | ||
| 2Assistant Professor, Jundi-Shapur University of Technology, Dezful, Iran, | ||
| 3Department of Electrical Engineering, Faculty of Engineering, Ayatollah Boroujerdi University, Boroujerd, Iran | ||
| 4Master of Electrical Engineering, Planning and Management of Electrical Energy Systems, Ayatollah Boroujerdi University, Iran | ||
| چکیده | ||
| Objective: Three-phase boost rectifier is a Voltage-Source Converter that converts three-phase AC input voltage to a higher DC voltage. In this paper, an artificial intelligent-based system, with learning and adapting ability, is designed for using in the two voltage-based control methods of rectifiers, with the names of Voltage Oriented Control (VOC) and Direct Power Control (DPC). For implementation of this intelligent controller a hybrid structure of the Fuzzy Logic (FL) and Neural Networks (NN) that named as Adaptive Network-based Fuzzy Inference System (ANFIS) is used. Among the common network training algorithms, the error back propagation algorithm is known as the most common solution by providing an efficient computational method, so in this article, the above method is used to design the controller. This neuro-fuzzy-based control model is applicable in both VOC and DPC methods and increases the correctness of the output current and DC voltage with low ripple, short settling time and also dynamic operation. The implementation of the proposed controller is simple and requires only 49 fuzzy rules. Compared to other controllers whose structure is neural network and fuzzy, it has fewer layers and its accuracy is higher. | ||
| کلیدواژهها | ||
| Learning؛ ANFIS؛ Rectifier؛ Inference | ||
| مراجع | ||
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