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Article

Advanced Strategy of Speed Predictive Control for Nonlinear Synchronous Reluctance Motors

1
Institute for Electrical Drive Systems and Power Electronics, Technical University of Munich (TUM), 80333 München, Germany
2
Electrical Engineering Department, Faculty of Engineering, Fayoum University, Fayoum 63514, Egypt
3
Electrical Engineering Department, Faculty of Engineering, Assiut University, Assiut 71516, Egypt
4
Department of Electrical Engineering and Information Technology, Munich University of Applied Sciences, 80335 München, Germany
5
Electrical Engineering Department, Faculty of Engineering, Cairo University, Cairo 12613, Egypt
*
Author to whom correspondence should be addressed.
Machines 2020, 8(3), 44; https://doi.org/10.3390/machines8030044
Submission received: 7 July 2020 / Revised: 17 July 2020 / Accepted: 30 July 2020 / Published: 1 August 2020
(This article belongs to the Special Issue Design and Control of Rotating Electrical Machines)

Abstract

To gain fast dynamic response, high performance, and good tracking capability, several control strategies have been applied to synchronous reluctance motors (SynRMs). In this paper, a nonlinear advanced strategy of speed predictive control (SPC) based on the finite control set model predictive control (FCS-MPC) is proposed and simulated for nonlinear SynRMs. The SPC overcomes the limitation of the cascaded control structure of the common vector control by employing a novel strategy that considers all the electrical and mechanical variables in one control law through a new cost function to obtain the switching signals for the power converter. The SynRM flux maps are known based on finite element method (FEM) analysis to take into consideration the effect of the nonlinearity of the machine. To clear the proposed strategy features, a functional and qualitative comparison between the proposed SPC, field-oriented control (FOC) with an anti-windup scheme, and current predictive control (CPC) with outer PI speed control loop is presented. For simplicity, particle swarm optimization (PSO) is performed to tune all the unknown parameters of the control strategies. The comparison features include controller design, dynamic and steady-state behaviors. Simulation results are presented to investigate the benefits and limitations of the three control strategies. Finally, the proposed SPC, FOC, and CPC have their own merits, and all methods encounter the requirements of advanced high-performance drives.
Keywords: synchronous reluctance motor; speed predictive control; field-oriented control; current predictive control; particle swarm optimization synchronous reluctance motor; speed predictive control; field-oriented control; current predictive control; particle swarm optimization

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MDPI and ACS Style

Farhan, A.; Abdelrahem, M.; Hackl, C.M.; Kennel, R.; Shaltout, A.; Saleh, A. Advanced Strategy of Speed Predictive Control for Nonlinear Synchronous Reluctance Motors. Machines 2020, 8, 44. https://doi.org/10.3390/machines8030044

AMA Style

Farhan A, Abdelrahem M, Hackl CM, Kennel R, Shaltout A, Saleh A. Advanced Strategy of Speed Predictive Control for Nonlinear Synchronous Reluctance Motors. Machines. 2020; 8(3):44. https://doi.org/10.3390/machines8030044

Chicago/Turabian Style

Farhan, Ahmed, Mohamed Abdelrahem, Christoph M. Hackl, Ralph Kennel, Adel Shaltout, and Amr Saleh. 2020. "Advanced Strategy of Speed Predictive Control for Nonlinear Synchronous Reluctance Motors" Machines 8, no. 3: 44. https://doi.org/10.3390/machines8030044

APA Style

Farhan, A., Abdelrahem, M., Hackl, C. M., Kennel, R., Shaltout, A., & Saleh, A. (2020). Advanced Strategy of Speed Predictive Control for Nonlinear Synchronous Reluctance Motors. Machines, 8(3), 44. https://doi.org/10.3390/machines8030044

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