{"id":"W3114807490","doi":"10.1109/tec.2020.3047983","title":"A Review of Predictive Control Techniques for Switched Reluctance Machine Drives. Part I: Fundamentals and Current Control","year":2020,"lang":"en","type":"review","venue":"IEEE Transactions on Energy Conversion","topic":"Multilevel Inverters and Converters","field":"Engineering","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Agencia Nacional de Investigación y Desarrollo; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Switched reluctance motor; Model predictive control; Control engineering; Control (management); Computer science; Current (fluid); Machine control; Control theory (sociology); Engineering; Artificial intelligence; Rotor (electric); Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001259118,0.0005676508,0.001874171,0.000177189,0.00007959483,0.00001448898,0.0002170944,0.0002044694,0.00007199797],"category_scores_gemma":[0.000005344022,0.0005052856,0.0006399829,0.000184147,0.00009083228,0.0001163973,0.000002025951,0.0003556989,0.000004284792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001989265,"about_ca_system_score_gemma":0.00007686379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000145063,"about_ca_topic_score_gemma":0.000002611696,"domain_scores_codex":[0.9981904,0.000104266,0.0007715867,0.0004675904,0.000199957,0.0002662126],"domain_scores_gemma":[0.9989364,0.0002335184,0.0002650672,0.00030985,0.00008100485,0.000174126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005950266,0.00004680911,1.037106e-7,0.05471754,0.0004872035,0.000002216424,0.00001845809,0.00003499876,0.00001769835,0.000009794768,0.001961723,0.9426439],"study_design_scores_gemma":[0.001074264,0.0002077312,6.183505e-8,0.05840728,0.001672345,0.000009510937,0.000005672346,0.05000629,0.0004145855,0.000005274957,0.8877935,0.0004034287],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[4.431536e-8,0.5393667,0.4582786,0.00002922586,0.0005086479,0.0008121243,0.0008589783,0.0001254362,0.00002021187],"genre_scores_gemma":[0.001892689,0.9963937,0.000130959,0.0004041341,0.00006785014,0.0009211791,0.00007042912,0.00008941918,0.0000296631],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9422405,"threshold_uncertainty_score":0.9997399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01852979397035864,"score_gpt":0.2578629355756809,"score_spread":0.2393331416053223,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}