{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,5]],"date-time":"2025-04-05T04:18:33Z","timestamp":1743826713003,"version":"3.40.3"},"reference-count":35,"publisher":"Walter de Gruyter GmbH","issue":"5","license":[{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>This paper investigates an optimal model-free control design for a synchronous reluctance motor (Syn-RM) with unknown nonlinear dynamic functions, parameter variations, and disturbances. The idea is to combine a predictive control with a time-delay estimation technique (TDE) in order to successfully deal with the system\u2019s uncertainties and make the Syn-RM control scheme easy to implement in real-time. This model-free control strategy comprises two cascade control loops namely outer and inner loops. The outer loop is designed for the mechanical part of Syn-RM to ensure the convergence of the speed dynamics by using a proportional-integral controller while the inner loop is developed to control the uncertain dynamics of currents via an optimal robust controller. In the proposed current loop, the predictive control is enhanced by the inclusion of ultra-local model theory where dynamic functions and disturbances are estimated by instantaneous input-output measurements of the Syn-RM using the TDE approach. Moreover, a particle swarm optimization (PSO) algorithm is also proposed to find the optimal design parameters to improve the dynamic performances of the closed-loop control system. Numerical validation tests of the proposed TDE-based model-free predictive current control (TDE-MFPCC) method are performed in the simulation environment of the Syn-RM system, and the results show the robustness and the effectiveness of the proposed TDE-MFPCC compared to the conventional model-based PCC.<\/jats:p>","DOI":"10.2478\/jee-2023-0042","type":"journal-article","created":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T03:42:09Z","timestamp":1697859729000},"page":"344-356","source":"Crossref","is-referenced-by-count":0,"title":["Model-free predictive current control of Syn-RM based on time delay estimation approach"],"prefix":"10.2478","volume":"74","author":[{"given":"Mohamed Essalih","family":"Boussouar","sequence":"first","affiliation":[{"name":"Laboratoire de Mod\u00e9lisation des Syst\u00e8mes \u00c9nerg\u00e9tiques, LMSE . University of Biskra , Biskra , Algeria"},{"name":"CISE \u2013 Electromechatronic Systems Research Centre , University of Beira Interior , Covilh\u00e3 , Portugal"}]},{"given":"Abdelghani","family":"Chelihi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, LI3CUB Laboratory , University of Biskra , Biskra , Algeria"},{"name":"Department of Electronics, Faculty of Technology , Contantine 1 University , Constantine , Algeria"}]},{"given":"Khaled","family":"Yahia","sequence":"additional","affiliation":[{"name":"CISE \u2013 Electromechatronic Systems Research Centre , University of Beira Interior , Covilh\u00e3 , Portugal"},{"name":"Laboratoire de G\u00e9nie Energ\u00e9tique et Mat\u00e9riaux, LGEM , University of Biskra , Biskra , Algeria"}]},{"given":"Antonio J. Marques","family":"Cardoso","sequence":"additional","affiliation":[{"name":"CISE \u2013 Electromechatronic Systems Research Centre , University of Beira Interior , Covilh\u00e3 , Portugal"}]}],"member":"374","published-online":{"date-parts":[[2023,10,21]]},"reference":[{"key":"2025040114585081740_j_jee-2023-0042_ref_001","doi-asserted-by":"crossref","unstructured":"T. Hamiti, T. Lubin, L. Baghli, and A. Rezzoug, \u201cModeling of a synchronous reluctance machine accounting for space harmonics in view of torque ripple minimization,\u201d Mathematics and Computers in Simulation, vol. 81, no. 2, pp. 354-366, 2010.","DOI":"10.1016\/j.matcom.2010.07.024"},{"key":"2025040114585081740_j_jee-2023-0042_ref_002","doi-asserted-by":"crossref","unstructured":"G. H. B. Foo and X. Zhang, \u201cRobust direct torque control of synchronous reluctance motor drives in the field-weakening region,\u201d IEEE Transactions on Power Electronics, vol. 32, no. 2, pp. 1289-1298, 2017.","DOI":"10.1109\/TPEL.2016.2542241"},{"key":"2025040114585081740_j_jee-2023-0042_ref_003","doi-asserted-by":"crossref","unstructured":"H. Hadla and S. Cruz, \u201cPredictive stator flux and load angle control of synchronous reluctance motor drives operating in a wide speed range,\u201d IEEE Transactions on Industrial Electronics, vol. 64, no. 9, pp. 6950-6959, 2017.","DOI":"10.1109\/TIE.2017.2688971"},{"key":"2025040114585081740_j_jee-2023-0042_ref_004","doi-asserted-by":"crossref","unstructured":"S. E. Lyshevski, \u201cNonlinear modeling and robust control of synchronous reluctance motors,\u201d Energy Conversion and Management, vol. 43, no. 4, pp. 523-536, 2002.","DOI":"10.1016\/S0196-8904(01)00030-9"},{"key":"2025040114585081740_j_jee-2023-0042_ref_005","doi-asserted-by":"crossref","unstructured":"D. Igrec, A. Chowdhury, B. \u0160tumberger, and A. Sarja\u0161, \u201cRobust tracking system design for a synchronous reluctance motor \u2013 SynRM based on a new modified bat optimization algorithm,\u201d Applied Soft Computing, vol. 69, pp. 568-584, 2018.","DOI":"10.1016\/j.asoc.2018.05.002"},{"key":"2025040114585081740_j_jee-2023-0042_ref_006","doi-asserted-by":"crossref","unstructured":"L. Xu, X. Xu, T. Lipo, and D. Novotny, \u201cVector control of a synchronous reluctance motor including saturation and iron loss,\u201d IEEE Transactions on Industry Applications, vol. 27, no. 5, pp. 977-985, 1991.","DOI":"10.1109\/28.90356"},{"key":"2025040114585081740_j_jee-2023-0042_ref_007","doi-asserted-by":"crossref","unstructured":"T. Matsuo and T. Lipo, \u201cField oriented control of synchronous reluctance machine,\u201d in Proceedings of IEEE Power Electronics Specialist Conference - PESC \u201993, pp. 425-431, 1993.","DOI":"10.1109\/PESC.1993.471965"},{"key":"2025040114585081740_j_jee-2023-0042_ref_008","doi-asserted-by":"crossref","unstructured":"H. Hadla and F. Santos, \u201cPerformance comparison of field-oriented control, direct torque control, and model-predictive control for SynRMs,\u201d Chinese Journal of Electrical Engineering, vol. 8, no. 1, pp. 24-37, 2022.","DOI":"10.23919\/CJEE.2022.000003"},{"key":"2025040114585081740_j_jee-2023-0042_ref_009","doi-asserted-by":"crossref","unstructured":"C. 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