{"id":"W3021465811","doi":"10.1049/iet-epa.2019.0870","title":"Two‐vector based low‐complexity model predictive flux control for current‐source inverter‐fed induction motor drive","year":2020,"lang":"en","type":"article","venue":"IET Electric Power Applications","topic":"Multilevel Inverters and Converters","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Rockwell Automation (Canada); Toronto Metropolitan University","funders":"","keywords":"Induction motor; Control theory (sociology); Vector control; Inverter; Current (fluid); Model predictive control; Flux (metallurgy); Direct torque control; Computer science; Control (management); Control engineering; Engineering; Materials science; Electrical engineering; Voltage; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001938389,0.000380126,0.0003242191,0.0002362191,0.0002335158,0.0005062117,0.0005059714,0.0002953623,0.001259789],"category_scores_gemma":[0.0003429895,0.0001103478,0.000179692,0.0002817261,0.0002286157,0.0003555799,0.0001820219,0.0005537484,0.0001654209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002929039,"about_ca_system_score_gemma":0.0003484688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00242395,"about_ca_topic_score_gemma":0.002467105,"domain_scores_codex":[0.9998887,0.00001727654,0.000005789253,0.0000144827,0.0000634125,0.00001034217],"domain_scores_gemma":[0.9998937,0.00003899462,0.0000174232,0.00001198243,0.00003408064,0.000003802194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002483293,0.0001866352,0.0009239925,0.0005214696,0.0000614086,0.0001643205,0.0001461217,0.4515327,0.06289761,0.02186927,0.003739886,0.4577082],"study_design_scores_gemma":[0.00001335311,0.0001068839,0.0002707077,0.000009176258,0.000008968273,0.0000220346,0.000005837575,0.9891334,0.007377502,0.001214609,0.001830786,0.000006766509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02928874,0.0006651104,0.9622502,0.0001646298,0.00009706641,0.00004552722,0.00003507218,0.0009036723,0.006549887],"genre_scores_gemma":[0.9653336,0.0002693882,0.0320374,0.00003078944,0.00002902553,0.00004718022,0.00005490022,0.00002031244,0.002177458],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00242395,"threshold_uncertainty_score":0.004819691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02197545120636469,"score_gpt":0.2388295429803891,"score_spread":0.2168540917740244,"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."}}