{"id":"W3211552529","doi":"10.1109/iecon48115.2021.9589338","title":"Virtual-Flux Finite Control Set Model Predictive Control of Dual-Three Phase IPMSM Drives","year":2021,"lang":"en","type":"article","venue":"","topic":"Multilevel Inverters and Converters","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Control theory (sociology); Model predictive control; Inductance; Torque; Torque ripple; Computer science; Ripple; Direct torque control; Flux (metallurgy); MATLAB; Engineering; Control (management); Voltage; Physics; Induction motor; Materials science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007945547,0.0002479258,0.0004419984,0.00007654785,0.00003916812,0.00002667334,0.0001268335,0.0001225689,0.0006876637],"category_scores_gemma":[0.00003706364,0.0002373458,0.0001653093,0.0001079564,0.00006151173,0.0001946471,0.00001992243,0.000164317,0.00004038699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000364137,"about_ca_system_score_gemma":0.00006072285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001013053,"about_ca_topic_score_gemma":0.00003537229,"domain_scores_codex":[0.9987823,0.00002908248,0.0003907542,0.000259043,0.0002208239,0.00031803],"domain_scores_gemma":[0.9991672,0.0001534193,0.00004946366,0.0003452185,0.0001371296,0.0001475784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003466618,0.0002610544,0.0004821713,0.00009649248,0.001199641,0.00008545374,0.001770469,0.8260112,0.1122544,0.003144748,0.004658679,0.04968898],"study_design_scores_gemma":[0.007111827,0.0001059134,0.0002155692,0.00003334256,0.0001013975,0.000004164054,0.0002909372,0.9758172,0.01556365,0.0003863846,0.0001266426,0.0002429613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04938728,0.0001490751,0.9437183,0.00007954422,0.0002637392,0.0002387431,0.0003982472,0.0002117603,0.005553353],"genre_scores_gemma":[0.9979909,0.00001894991,0.0004128983,0.000423979,0.00004921352,0.00004743667,0.00004245963,0.00004120536,0.0009729387],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9486036,"threshold_uncertainty_score":0.9678681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01426395304929791,"score_gpt":0.2265449751364234,"score_spread":0.2122810220871255,"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."}}