Document Type : Research Articles
Authors
1 Department of Electrical Engineering, Shahid Beheshti University, Tehran, Iran
2 Assistant Professor, Jundi-Shapur University of Technology, Dezful, Iran,
3 Department of Electrical Engineering, Faculty of Engineering, Ayatollah Boroujerdi University, Boroujerd, Iran
4 Master of Electrical Engineering, Planning and Management of Electrical Energy Systems, Ayatollah Boroujerdi University, Iran
Abstract
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.
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[2] A. Zhetessov, G. Venkataramanan, “Systematic Adaptive Robust State Feedback Control for Active Front-End Rectifiers,” 2022 24th European Conference on Power Electronics and Applications (EPE'22 ECCE Europe), pp.1-11, 2022.
[3] A. Khan, M. Hosseinzadehtaher, M. B. Shadmand, S. Bayhan, H. Abu-Rub, “On the Stability of the Power Electronics-Dominated Grid: A New Energy Paradigm,”IEEE Industrial Electronics Magazine, vol.14, no.4, pp. 65-78, 2020.
[4] C. M. Emeghara, S. M. Mahajan, A. Arzani, “Direct Power Control of a Surface-Mounted Permanent Magnet Synchronous Generator Wind Turbine for Offshore Applications,” IEEE Access, vol.11, pp. 62409-62423, 2023.
[5] W. Ende and H. Shenghua, “Robust Control of the ThreePhase Voltage-Source PWM Rectifier Using EKF Load Current Observer,” Journal of Electrical Review, R. 89, pp. 189-193, NR 3a/2015.
[6] J. Hu, L. Shang, Y. He, and Z. Q. Zhu, “Direct Active and Reactive Power Regulation of Grid-Connected DC/AC Converters Using Sliding Mode Control Approach,” IEEE Trans. Power Electron., vol. 26, no. 2017.
[7] S. Maganti, N. P. Padhy, “Analysis and Design of PLL Less Current Control for Weak Grid-Tied LCL-Type Voltage Source Converter,” IEEE Journal of Emerging and Selected Topics in Power Electronics, vol.10, no.4, pp. 4026-4040, 2022
[8] S. Samanta, S. Barman, J. P. Mishra, P. Roy, B. K. Roy, “Design of an Interconnection and Damping AssignmentPassivity Based Control Technique for Energy Management and Damping Improvement of a DC Microgrid,” IET Generation, Transmission & Distribution, vol.14, no.11, pp. 2082-2091, 2020.
[9] Y. Gui, C. Kim, C. C. Chung, J. M. Guerrero, Y. Guan, and J. C. Vasquez, “Improved Direct Power Control for Grid-Connected Voltage Source Converters,” IEEE Trans. Ind. Electron., vol. 65, no. 10, pp. 8041–8051, 2018.
[10] L. Tai, M. Lin, H. Li, Y. Li, “A Novel Three-Vector-Based Model Predictive Direct Power Control for Three-Phase PWM Rectifier,” Electronics, 10 (21), Article number: 2579, 2021.
[11] J. Jang, “Self-Learning Fuzzy Controller Based on Temporal Back-Propagation,” IEEE Transaction on Neural Network, Vol. 3, pp.714-723, September 1992.
[12] A. Kumar and G. Srungavarapu “A Novel Voltage Sensorless DPC Approach of AFE Rectifier Based on Virtual Flux and Dynamic DC Link Reference Design,” 2016 IEEE Annual India Conf. (INDICON), Bangalore, 2016, pp. 1–6
[13] A. Baktash, A. Vahedi, and M. A. S. Masoum “New Switching Table for Improved Direct Power Control of Three-Phase PWM Rectifier,” Aust. J. Electr. Electron. Eng., 2015, 5, (2), pp. 161–167.
[14] C. Lin and Y. Lu, “A Neural Fuzzy System with Fuzzy Supervised Learning,” IEEE, Transaction on Systems, Man and Cybernetics, Vol. 26, No. 5, October 1996.
[15] M. R. Mosavi, A. Rahmati and A. Khoshsaadat, “Design of Efficient Adaptive Neuro-Fuzzy Controller Based on Supervisory Learning Capable for Speed and Torque Control of BLDC Botor,” PRZEGLÄ„D ELEKTROTECHNICZNY (Electrical Review), Vol. 88, pp. 238-246, 2012.
[16] S. Tano, T. Oyama and T. Arnould, “Deep Combination of Fuzzy Inference and Neural Network in Fuzzy Inference, Journal on Fuzzy Sets and Systems, Vol. 82, No. 2, pp.151-160, 1996.
[17] T. Takagi and M. Sugeno, “Fuzzy Identification of Systems and its Applications to Modeling and Control,” IEEE Transaction. On Systems, Man and Cybernetics, Vol. 15, pp. 116-132, 1985.
[18] A. Khoshsaadat, M. R. Mosavi, J. S. Moghani, A. Khoshooei, “Design of a Controller with ANFIS Architecture Attendant Learning Ability for SSSC-Based Damping Controller Applied in Single Machine Infinite Bus System,” Iranian Journal of Electrical and Electronic Engineering (IJEEE), Vol. 10, No. 3, pp. 212-222, 2014.
[19] Y. Q. Zhang, and A Kandel, “Compensatory Neuro-Fuzzy Systems With Fast Learning Algorithms,” IEEE Transaction on Neural Networks, Vol. 9, No. 1, January 1998.
[20] R. Zaheri, A. Khoshsaadat, J. S. Moghani. M. Abedi, “Fast Transient Hybrid Neuro-Fuzzy Controller for STATCOM During Unbalanced Voltage Sags,” AUT Journal of Electrical Engineering, Vol. 50, No. 1, pp. 67-74, 2018.
[21] R. Sivakumar, C. Sahana, P. A. Savitha, “Design of ANFIS-Based Estimation and Control for MIMO Systems,” International Journal of Engineering Research and Applications, Vol. 2, Issue 3, pp. 2803-2809, MayJun 2012.
[22] T. C. Lin and C. S. Lee, “Neural Network Based Fuzzy Logic Control and Decision System,” IEEE Transactions on Computers, Vol.40, No.12, pp.1320-1336, December 2009.
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