{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T15:57:07Z","timestamp":1768319827770,"version":"3.49.0"},"reference-count":47,"publisher":"Emerald","issue":"6","license":[{"start":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T00:00:00Z","timestamp":1606089600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["COMPEL"],"published-print":{"date-parts":[[2020,11,23]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to present the Moore-Penrose pseudoinverse (PI) modeling and compare with artificial neural network (ANN) modeling for switched reluctance machine (SRM) performance.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>In a design of an SRM, there are a number of parameters that are chosen empirically inside a certain interval, therefore, to find an optimal geometry it is necessary to define a good model for SRM. The proposed modeling uses the Moore-Penrose PI for the resolution of linear systems and finite element simulation data. To attest to the quality of PI modeling, a model using ANN is established and the two models are compared with the values determined by simulations of finite elements.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The proposed PI model showed better accuracy, generalization capacity and lower computational cost than the ANN model.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>The proposed approach can be applied to any problem as long as experimental\/computational results can be obtained and will deliver the best approximation model to the available data set.<\/jats:p><\/jats:sec>","DOI":"10.1108\/compel-11-2019-0449","type":"journal-article","created":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T06:37:40Z","timestamp":1606113460000},"page":"1411-1430","source":"Crossref","is-referenced-by-count":3,"title":["Moore-Penrose pseudo-inverse and artificial neural network modeling in performance prediction of switched reluctance machine"],"prefix":"10.1108","volume":"39","author":[{"given":"Ana Camila","family":"Ferreira Mamede","sequence":"first","affiliation":[]},{"given":"Jos\u00e9 Roberto","family":"Camacho","sequence":"additional","affiliation":[]},{"given":"Rui Esteves","family":"Ara\u00fajo","sequence":"additional","affiliation":[]},{"given":"Igor Santos","family":"Peretta","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"issue":"5","key":"key2020121516191014900_ref001","doi-asserted-by":"crossref","first-page":"1883","DOI":"10.1109\/TMAG.1985.1063910","article-title":"Magnetic field analysis of a switched reluctance motor using a two dimensional finite element model","volume":"21","year":"1985","journal-title":"IEEE Transactions on Magnetics"},{"key":"key2020121516191014900_ref002","first-page":"1854","article-title":"Artificial neural network modeling of synchronous reluctance motor","year":"2011"},{"issue":"1\/2","key":"key2020121516191014900_ref003","first-page":"146","article-title":"The Moore\u2013Penrose pseudoinverse: a tutorial review of the theory","volume":"42","year":"2011","journal-title":"Brazilian Journal of Physics"},{"key":"key2020121516191014900_ref004","volume-title":"Generalized Inverses: Theory and Applications (CMS Books in Mathematics)","year":"2003"},{"issue":"1","key":"key2020121516191014900_ref005","first-page":"23","article-title":"Geometry design of switched reluctance motor to reduce the torque ripple by finite element method and sensitive analysis","volume":"1","year":"2016","journal-title":"Journal of Electric Power & Energy Conversion Systems"},{"issue":"5","key":"key2020121516191014900_ref006","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1016\/j.talanta.2008.05.019","article-title":"Response surface methodology (RSM) as a tool for optimization in analytical chemistry","volume":"76","year":"2008","journal-title":"Talanta"},{"key":"key2020121516191014900_ref007","first-page":"23","article-title":"Bayesian regularization of neural networks","volume-title":"Methods in Molecular BiologyTM","year":"2008"},{"issue":"2","key":"key2020121516191014900_ref008","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1061\/(ASCE)CP.1943-5487.0000266","article-title":"Efficient method for Moore-Penrose inverse problems involving symmetric structures based on group theory","volume":"28","year":"2014","journal-title":"Journal of Computing in Civil Engineering"},{"issue":"3","key":"key2020121516191014900_ref009","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1049\/ip-epa:20045207","article-title":"Simplified flux-linkage model for switched-reluctance motors","volume":"152","year":"2005","journal-title":"IEE Proceedings \u2013 Electric Power Applications"},{"issue":"3","key":"key2020121516191014900_ref010","article-title":"Design of experiments application, concepts, examples: state of the art","volume":"5","year":"2017","journal-title":"Periodicals of Engineering and Natural Sciences (Pen)"},{"key":"key2020121516191014900_ref011","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.neucom.2016.02.076","article-title":"Torque modeling of switched reluctance motor using LSSVM-DE","volume":"211","year":"2016","journal-title":"Neurocomputing"},{"issue":"2","key":"key2020121516191014900_ref012","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.aca.2007.07.011","article-title":"Box-Behnken design: an alternative for the optimization of analytical methods","volume":"597","year":"2007","journal-title":"Analytica Chimica Acta"},{"key":"key2020121516191014900_ref013","article-title":"Optimization design of switched reluctance motor based on particle swarm optimization","volume-title":"2011 International Conference on Electrical Machines and Systems","year":"2011"},{"key":"key2020121516191014900_ref014","volume-title":"Numerical Methods for Engineers: A Programming Approach","year":"1991"},{"issue":"1","key":"key2020121516191014900_ref015","first-page":"129","article-title":"Application of the generalized inverse to the geometrically nonlinear problems","volume":"6","year":"1981","journal-title":"Solid Mech. Arch"},{"issue":"10","key":"key2020121516191014900_ref016","doi-asserted-by":"crossref","first-page":"8781","DOI":"10.1063\/1.1556987","article-title":"Modeling of switched reluctance motor using Fourier series for performance analysis","volume":"93","year":"2003","journal-title":"Journal of Applied Physics"},{"issue":"1","key":"key2020121516191014900_ref017","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/00224065.2011.11917841","article-title":"A class of three-level designs for definitive screening in the presence of second-order effects","volume":"43","year":"2011","journal-title":"Journal of Quality Technology"},{"issue":"2","key":"key2020121516191014900_ref018","doi-asserted-by":"crossref","first-page":"20","DOI":"10.3390\/mca21020020","article-title":"Predictive abilities of Bayesian regularization and Levenberg\u2013Marquardt algorithms in artificial neural networks: a comparative empirical study on social data","volume":"21","year":"2016","journal-title":"Mathematical and Computational Applications"},{"issue":"10","key":"key2020121516191014900_ref019","doi-asserted-by":"crossref","first-page":"4179","DOI":"10.1109\/TMAG.2011.2151183","article-title":"B-spline neural network approach to inverse problems in switched reluctance motor optimal design","volume":"47","year":"2011","journal-title":"IEEE Transactions on Magnetics"},{"key":"key2020121516191014900_ref020","volume-title":"Switched Reluctance Motor Drives","year":"2001"},{"issue":"7","key":"key2020121516191014900_ref021","doi-asserted-by":"crossref","first-page":"07F103","DOI":"10.1063\/1.3062962","article-title":"Artificial neural network based torque calculation of switched reluctance motor without locking the rotor","volume":"105","year":"2009","journal-title":"Journal of Applied Physics"},{"issue":"4","key":"key2020121516191014900_ref022","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1049\/ip-b.1980.0034","article-title":"Variable-speed switched reluctance motors","volume":"127","year":"1980","journal-title":"IEE Proceedings B Electric Power Applications"},{"issue":"2","key":"key2020121516191014900_ref023","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1109\/TEC.2003.811738","article-title":"Neural network-based modeling and parameter identification of switched reluctance motors","volume":"18","year":"2003","journal-title":"IEEE Transactions on Energy Conversion"},{"issue":"31\/32","key":"key2020121516191014900_ref024","first-page":"2194","article-title":"Geometrically non-linear force method for assemblies with infinitesimal mechanisms","volume":"84","year":"2006","journal-title":"Computers and Structures"},{"key":"key2020121516191014900_ref025","unstructured":"MacAusland, R. (2014), \u201cThe Moore-Penrose inverse and least squares\u201d, available at: http:\/\/buzzard.ups.edu\/courses\/2014spring\/420projects\/math420-UPS-spring-2014-macausland-pseudo-inverse.pdf"},{"issue":"3","key":"key2020121516191014900_ref026","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1109\/TEC.2015.2411677","article-title":"Multiobjective optimization of switched reluctance motors based on design of experiments and particle swarm optimization","volume":"30","year":"2015","journal-title":"IEEE Transactions on Energy Conversion"},{"issue":"16","key":"key2020121516191014900_ref027","first-page":"674","article-title":"Switched reluctance machine modeling through multilayer neural networks","volume":"1","year":"2018","journal-title":"Renewable Energy and Power Quality Journal (RE&PQJ)"},{"issue":"4","key":"key2020121516191014900_ref028","doi-asserted-by":"crossref","first-page":"71","DOI":"10.3390\/machines7040071","article-title":"Influence of geometric dimensions on the performance of switched reluctance machine","volume":"7","year":"2019","journal-title":"Machines"},{"issue":"3","key":"key2020121516191014900_ref029","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1016\/j.aej.2013.06.007","article-title":"Artificial neural network and response surface methodology modeling in mass transfer parameters predictions during osmotic dehydration of Carica papaya l","volume":"52","year":"2013","journal-title":"Alexandria Engineering Journal"},{"key":"key2020121516191014900_ref030","volume-title":"Neural Network Toolbox 7 User\u2019s Guide","year":"2010"},{"issue":"3","key":"key2020121516191014900_ref031","doi-asserted-by":"crossref","first-page":"1524","DOI":"10.1109\/20.999126","article-title":"Multiobjective optimization method based on a genetic algorithm for switched reluctance motor design","volume":"38","year":"2002","journal-title":"IEEE Transactions on Magnetics"},{"key":"key2020121516191014900_ref032","first-page":"727","article-title":"Design using finite element analysis of switched reluctance motor for electric vehicle","volume-title":"Information and Communication Technologies, 2006. ICTTA \u201806. 2nd","year":"2006"},{"key":"key2020121516191014900_ref033","unstructured":"Peretta, I.S. (2015), \u201cEvolution of differential models for concrete systems through genetic programming\u201d, Phd thesis, Universidade Federal de Uberl\u00e2ndia."},{"key":"key2020121516191014900_ref034","volume-title":"Design of Rotating Electrical Machines","year":"2014"},{"key":"key2020121516191014900_ref035","volume-title":"Scientific Computing with MATLAB and Octave (Texts in Computational Science and Engineering)","year":"2006"},{"issue":"6","key":"key2020121516191014900_ref036","doi-asserted-by":"crossref","first-page":"4473","DOI":"10.1109\/20.809140","article-title":"Analytical calculation of the switched reluctance motor\u2019s unaligned inductance","volume":"35","year":"1999","journal-title":"IEEE Transactions on Magnetics"},{"issue":"4","key":"key2020121516191014900_ref037","doi-asserted-by":"crossref","first-page":"1996","DOI":"10.1109\/20.875277","article-title":"Analytically computing the flux linked by a switched reluctance motor phase when the stator and rotor poles overlap","volume":"36","year":"2000","journal-title":"IEEE Transactions on Magnetics"},{"issue":"3","key":"key2020121516191014900_ref038","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1109\/7.953252","article-title":"Simulation of a 6\/4 switched reluctance motor based on Matlab\/Simulink environment","volume":"37","year":"2001","journal-title":"IEEE Transactions on Aerospace and Electronic Systems"},{"key":"key2020121516191014900_ref039","doi-asserted-by":"crossref","first-page":"279","DOI":"10.2528\/PIERM12103001","article-title":"Two simple analytical models, direct and inverse, for switched reluctance motors","volume":"29","year":"2013","journal-title":"Progress in Electromagnetics Research M"},{"key":"key2020121516191014900_ref040","first-page":"1","article-title":"A generalized inverse procedure for model structure identification","year":"2000","journal-title":"Joint Conf. on Water Resource Engineering and Water Resources Planning and Management"},{"issue":"2","key":"key2020121516191014900_ref041","doi-asserted-by":"crossref","first-page":"759","DOI":"10.3233\/IFS-130766","article-title":"Non-linear flux linkage modeling of switched reluctance machine using MVNLR and ANFIS","volume":"26","year":"2014","journal-title":"Journal of Intelligent and Fuzzy Systems"},{"key":"key2020121516191014900_ref042","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1109\/ICEMS12746.2007.4412081","article-title":"Influence of the switched reluctance machines design parameters on its steady-state operation characteristics","volume-title":"2007 International Conference on Electrical Machines and Systems (ICEMS)","year":"2007"},{"issue":"9","key":"key2020121516191014900_ref043","doi-asserted-by":"crossref","first-page":"2980","DOI":"10.1109\/TIE.2010.2051390","article-title":"Multi-objective optimization design of in-wheel switched reluctance motors in electric vehicles","volume":"57","year":"2010","journal-title":"IEEE Transactions on Industrial Electronics"},{"key":"key2020121516191014900_ref044","volume-title":"Applied Numerical Methods Using MATLAB","year":"2005"},{"issue":"1","key":"key2020121516191014900_ref045","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1061\/(ASCE)HY.1943-7900.0000475","article-title":"Pipe friction parameters identification method based on Moore-Penrose pseudo-inverse solution","volume":"138","year":"2012","journal-title":"Journal of Hydraulic Engineering"},{"issue":"3","key":"key2020121516191014900_ref046","first-page":"195","article-title":"Kinematic analysis of deployable toroidal spatial truss structures for large mesh antenna","volume":"46","year":"2005","journal-title":"Journal of the International Association for Shell and Spatial Structures"},{"key":"key2020121516191014900_ref047","unstructured":"Zontini, D.D. (2014), \u201cM\u00e9todos computacionais Para inversas generalizadas\u201d, Phd thesis, Universidade Federal do Paran\u00e1."}],"container-title":["COMPEL - The international journal for computation and mathematics in electrical and electronic engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/COMPEL-11-2019-0449\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/COMPEL-11-2019-0449\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T23:16:26Z","timestamp":1753398986000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/compel\/article\/39\/6\/1411-1430\/76591"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,23]]},"references-count":47,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2020,11,23]]}},"alternative-id":["10.1108\/COMPEL-11-2019-0449"],"URL":"https:\/\/doi.org\/10.1108\/compel-11-2019-0449","relation":{},"ISSN":["0332-1649","0332-1649"],"issn-type":[{"value":"0332-1649","type":"print"},{"value":"0332-1649","type":"print"}],"subject":[],"published":{"date-parts":[[2020,11,23]]}}}