Sensorless control of switched reluctance motors through artificial neural network with a fuzzy interface

NAMALA RANJITKUMAR NAMALA; Kuthuri Narasimha Raju

doi:10.32397/tesea.vol6.n2.674

Authors

Namala Ranjitkumar Department of Electrical and Electronics Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India https://orcid.org/0009-0000-5307-858X
Kuthuri Narasimha Raju Department of Electrical and Electronics Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India

DOI:

https://doi.org/10.32397/tesea.vol6.n2.674

Keywords:

8/6 SRM, Sensorless scheme, Fuzzy Estimator, ANFIS Estimator, ANN Estimator

Abstract

Switched resistance motors, are becoming increasingly used in industrial and hybrid electric vehicle (HEV) applications. But improving SRM performance is still a crucial field for study, especially with regard to their inherent benefit of accurate rotor position estimate, which is closely related to operational effectiveness. Rotor position sensing has traditionally required the incorporation of specialized sensors, which has led to difficulties like increased costs, complicated alignment, limited size, and maintenance requirements. In order to overcome these constraints, this work promotes the creation of sensorless motor control schemes that make use of cutting edge Artificial intelligence methods such as fuzzy logic and Adaptive Neuro-Fuzzy Inference System (ANFIS).To provide robust control, the suggested sensorless control systems make use of inputs such bus voltage, rotor speeds, torque instructions, and SRM parameters. The effectiveness of these methods is thoroughly assessed by painstaking simulation experiments, confirming their capacity to attain accurate control and high-performance operation. To further illuminate the benefits of sensorless control implementations, this research also does a comparison analysis between the two suggested soft computing approaches and their sensor-based equivalents. In the end, this research advances the field of SRM technology, opening the door to more dependable, economical, and efficient motor control systems in a variety of industrial and automotive applications.

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References

R. Krishnan. Switched reluctance motor drives: Modeling, simulation, analysis, design, and applications, December 2017.

G.S. Buja, R. Menis, and M.I. Valla. Variable structure control of an srm drive. IEEE Transactions on Industrial Electronics, 40(1):56–63, 1993.

G. Gallegos-Lopez, P.C. Kjaer, and T.J.E. Miller. High-grade position estimation for srm drives using flux linkage/current correction model. IEEE Transactions on Industry Applications, 35(4):859–869, 1999.

R. A. Gupta, Rajesh Kumar, and S.K. Bishnoi. Sensorless control of switched reluctance motor drive with fuzzy logic based rotor position estimation. International Journal of Computer Applications, 1(22):74–81, February 2010.

Xiu Jie and Xia Changliang. An application of fuzzy logic controller for switched reluctance motor drive. In 2007 Chinese Control Conference, page 50–53. IEEE, July 2006.

E. Mese and D.A. Torrey. An approach for sensorless position estimation for switched reluctance motors using artifical neural networks. IEEE Transactions on Power Electronics, 17(1):66–75, January 2002.

H. Gao, F.R. Salmasi, and M. Ehsani. Inductance model-based sensorless control of the switched reluctance motor drive at low speed. IEEE Transactions on Power Electronics, 19(6):1568–1573, November 2004.

Rajesh Kumar, R. A. Gupta, Sachin Goyal, and S. K. Bishnoi. Fuzzy tuned pid controller based pfc converter-inverter fed srm drive. In 2006 IEEE International Conference on Industrial Technology, page 2498–2503. IEEE, 2006.

P.P. Acarnley and J.F. Watson. Review of position-sensorless operation of brushless permanent-magnet machines. IEEE Transactions on Industrial Electronics, 53(2):352–362, April 2006.

Chang-Liang Xia and Jie Xiu. Sensorless Control of Switched Reluctance Motor Based on ANFIS, page 645–653. Springer Berlin Heidelberg, 2006.

R. Krishnan, S.-Y. Park, and K. Ha. Theory and operation of a four-quadrant switched reluctance motor drive with a single controllable switch—the lowest cost four-quadrant brushless motor drive. IEEE Transactions on Industry Applications, 41(4):1047–1055, July 2005.

Pratap Sekhar Puhan, Pravat Kumar Ray, and Gayadhar Panda. Development of real time implementation of 5/5 rule based fuzzy logic controller shunt active power filter for power quality improvement. International Journal of Emerging Electric Power Systems, 17(6):607–617, December 2016.

G.C.D. Sousa and B.K. Bose. A fuzzy set theory based control of a phase-controlled converter dc machine drive. IEEE Transactions on Industry Applications, 30(1):34–44, 1994.

Jayanta Mukhopadhyay, Sumana Choudhury, and Samarjit Sengupta. Anfis based speed and current controller for switched reluctance motor. In 2021 IEEE 4th International Conference on Computing, Power and Communication Technologies (GUCON), page 1–6. IEEE, September 2021.

Hady Abdel Maksoud and Mohamed S. Zaky. Stator flux based-mras position/speed observer of sensorless switched reluctance motor drives including startup operation. Ain Shams Engineering Journal, 16(1):103199, January 2025.

Xiaodong Sun, Zhengxiong Xu, Mingzhang Pan, Chao Sun, Wei Pan, and Gang Lei. Sensorless control strategy for srm based on flux linkage in medium to high-speed range. IEEE Transactions on Industrial Electronics, 72(10):9922–9930, October 2025.

Galina Demidova, Jackson J. Justo, Dmitry Lukichev, Nikolai Poliakov, and Alecksey Anuchin. Neural network models for predicting magnetization surface switched reluctance motor: Classical, radial basis function, and physics-informed techniques. IEEE Access, 13:54987–54996, 2025.

Amarnath Yalavarthi and Bhim Singh. Sensorless speed control of srm drive using optimized neural network model for rotor position estimation. IEEE Transactions on Energy Conversion, 39(4):2158–2168, December 2024.

M. Ehsani, I. Husain, S. Mahajan, and K.R. Ramani. New modulation encoding techniques for indirect rotor position sensing in switched reluctance motors. IEEE Transactions on Industry Applications, 30(1):85–91, 1994.