Switched Reluctance Motor Drive Controller Design using Adaptive Neuro-Fuzzy Controller
Keywords:
Torque ripple, Switched Reluctance Motor (SRM), Fuzzy Logic Control (FLC), Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN)Abstract
Switched reluctance motors (SRM) has dominant features like simple structure and robustness has raised quest among the researchers to make them suitable even in fault tolerant, poor operating conditions and employed for high- performance motion control applications. However, SRM possess higher torque ripple due to presence of flux harmonics in the air gap which reduces the functionality of the high- performance drive applications compared to other conventional drives. This paper intent at the torque ripples minimization (TRM) of SRM drive using Adaptive Neuro-Fuzzy Inference System (ANFIS). Artificial Neural Network (ANN), Fuzzy Logic Control (FLC) and ANFIS controllers are designed and simulated using Matlab/Simulink.The results of the simulations demonstrate that the considered ANFIS controller produces an excellent dynamic performance of the machine. The performance of ANN & ANFIS based techniques is superior to FLC based controller. Owing to the strong learning & generalization characteristics, ANFIS performs better than ANN & FLC, which enhances the dynamic performance of SRM drives. ANFIS gives improved performance than ANN and FLC due to its good learning and generalization capabilities thereby improves the dynamic characteristics of the SR Motor based drives.
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Li C, Zhang C, Liu J, Bian D. A High-Performance Indirect Torque Control Strategy for Switched Reluctance Motor Drives. Mathematical Problems in Engineering. 2021 Feb 16;2021.
Ren P, Zhu J, Jing Z, Guo Z, Xu A. Minimization of torque ripple in switched reluctance motor based on MPC and TSF. IEEJ Transactions on Electrical and Electronic Engineering. 2021.
Sial MR, Sahoo NC,“Second-Order Generalized Integrator-Based Proportional-Resonant Current Controller for Torque Ripple Minimization in Switched Reluctance Motors” InProceedings of Symposium on Power Electronic and Renewable Energy Systems Control 2021 (pp. 43-53). Springer, Singapore.
Khachane AV, Dhamse SS. Torque Ripple Minimization of Switched Reluctance Motor and Comparison of Controllers for Electric Vehicle Applications. In2020 International Conference on Convergence to Digital World-Quo Vadis (ICCDW) 2020 Feb 18 (pp. 1-6). IEEE.
Hui C, Li M, Hui W, Shen SQ, Wang W. Torque ripple minimization for switched reluctance motor with predictive current control method. In2017 20th International Conference on Electrical Machines and Systems (ICEMS) 2017 Aug 11 (pp. 1-4). IEEE.
Martin GW, Kumar CA. Novel Bio-Inspired Algorithm for Speed Control and Torque Ripple Reduction of Switched Reluctance Motor in Aerospace Application. Journal of Electrical Engineering & Technology. 2021 May;16(3):1359-74.
Reddy AV, Kumar BM. Torque ripple minimization of switched reluctance motor using pole embrace and pole configuration methods. International Journal of Applied Engineering Research. 2018;13(10):8525-9.
Vidhya H, Allirani S. Design and Hardware Implementation of Switched Reluctance Motor Using ANSYS Maxwell. InAdvances in Electrical and Computer Technologies: Select Proceedings of ICAECT 2020 2021 (pp. 875-887). Springer Singapore.
Xue XD, Cheng KW, Ho SL. Optimization and evaluation of torque-sharing functions for torque ripple minimization in switched reluctance motor drives. IEEE transactions on power electronics. 2009 Aug 25;24(9):2076-90.
Rana AK, Raviteja AV. A Mathematical Torque Ripple Minimization Technique Based on Nonlinear Modulating Factor for Switched Reluctance Motor Drives. IEEE Transactions on Industrial Electronics. 2021 Mar 10.
Ye J, Bilgin B, Emadi A. An extended-speed low-ripple torque control of switched reluctance motor drives. IEEE Transactions on Power Electronics. 2014 Apr 14;30(3):1457-70.
Bostanci E, Moallem M, Parsapour A, Fahimi B. Opportunities and challenges of switched reluctance motor drives for electric propulsion: A comparative study. IEEE transactions on transportation electrification. 2017 Jan 9;3(1):58-75.
Evangeline SJ, Kumar SS. Torque ripple minimization of switched reluctance drives-A survey. In5th IET International Conference on Power Electronics, Machines and Drives (PEMD 2010) 2010 Apr 19 (pp. 1-6). IET.
Inanc N, Ozbulur V. Torque ripple minimization of a switched reluctance motor by using continuous sliding mode control technique. Electric Power Systems Research. 2003 Sep 1;66(3):241-51.
Üstün O, Önder M. An improved torque sharing function to minimize torque ripple and increase average torque for switched reluctance motor drives. Electric Power Components and Systems. 2020 Aug 6;48(6-7):667-81.
Mohammadi F, Molaei M, Afra O. Power optimization and ripple minimization in switched reluctance motor drives of small modular reactor and a comparison with a permanent magnet motor. Progress in Nuclear Energy. 2021 Jun 18:103843.
Lee CH, Kirtley J, Angle M, Tahour A. Switched reluctance motor drives for hybrid electric vehicles. Switched Reluctance Motor-Concept, Control and Applications. 2017 Jun 21.
Harikrishnan R, Fernandez FM. Improved online torque-sharing-function based low ripple torque control of switched reluctance motor drives. In2016 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES) 2016 Dec 14 (pp. 1-6). IEEE.
Guettaf A, Benchabane F, Bahri M, Bennis O. Torque ripple minimization in switched reluctance motor using the fuzzy logic control technique. International Journal of System Assurance Engineering and Management. 2014 Dec;5(4):679-85.
Chowdhury SM, Harasis S, Gundogmus O, Vadamodala L, Das S, Sozer Y, Venegas F, Colavincenzo D. DC input current ripple minimization in switched reluctance machine drives. In2018 IEEE Energy Conversion Congress and Exposition (ECCE) 2018 Sep 23 (pp. 6110-6115). IEEE.
Ro HS, Kim DH, Jeong HG, Lee KB. Tolerant control for power transistor faults in switched reluctance motor drives. IEEE Transactions on Industry Applications. 2015 Mar 10;51(4):3187-97.
Pan JF, Cheung NC, Zou Y. An improved force distribution function for linear switched reluctance motor on force ripple minimization with nonlinear inductance modeling. IEEE transactions on magnetics. 2012 Oct 18;48(11):3064-7.
Yaseen, M., Hayder Sabah Salih, Mohammad Aljanabi, Ahmed Hussein Ali, & Saad Abas Abed. (2023). Improving Process Efficiency in Iraqi universities: a proposed management information system. Iraqi Journal For Computer Science and Mathematics, 4(1), 211–219. https://doi.org/10.52866/ijcsm.2023.01.01.0020
Aljanabi, M. ., & Sahar Yousif Mohammed. (2023). Metaverse: open possibilities. Iraqi Journal For Computer Science and Mathematics, 4(3), 79–86. https://doi.org/10.52866/ijcsm.2023.02.03.007
Atheel Sabih Shaker, Omar F. Youssif, Mohammad Aljanabi, ABBOOD, Z., & Mahdi S. Mahdi. (2023). SEEK Mobility Adaptive Protocol Destination Seeker Media Access Control Protocol for Mobile WSNs. Iraqi Journal For Computer Science and Mathematics, 4(1), 130–145. https://doi.org/10.52866/ijcsm.2023.01.01.0011
Hayder Sabah Salih, Mohanad Ghazi, & Aljanabi, M. . (2023). Implementing an Automated Inventory Management System for Small and Medium-sized Enterprises. Iraqi Journal For Computer Science and Mathematics, 4(2), 238–244. https://doi.org/10.52866/ijcsm.2023.02.02.021
Gabriel Santos, Natural Language Processing for Text Classification in Legal Documents , Machine Learning Applications Conference Proceedings, Vol 2 2022.
Gangula, R. ., Vutukuru, M. M. ., & Kumar M., R. . (2023). Network Intrusion Detection Method Using Stacked BILSTM Elastic Regression Classifier with Aquila Optimizer Algorithm for Internet of Things (IoT). International Journal on Recent and Innovation Trends in Computing and Communication, 11(2s), 118–131. https://doi.org/10.17762/ijritcc.v11i2s.6035
Anand, R., Ahamad, S., Veeraiah, V., Janardan, S.K., Dhabliya, D., Sindhwani, N., Gupta, A. Optimizing 6G wireless network security for effective communication (2023) Innovative Smart Materials Used in Wireless Communication Technology, pp. 1-20.
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