{"id":"W3138489062","doi":"10.18280/ejee.230108","title":"Hardware Implementation of Predictive Torque Control for an Induction Motor with Efficiency Optimization","year":2021,"lang":"en","type":"article","venue":"European Journal of Electrical Engineering","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Model predictive control; Induction motor; Torque; Direct torque control; Computer science; Control (management); Automotive engineering; Control theory (sociology); Engineering; Physics; Electrical engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002298915,0.0003709394,0.0003277095,0.0002769236,0.0002563227,0.0004720175,0.0008387975,0.0003271499,0.001891866],"category_scores_gemma":[0.0004278882,0.0001531683,0.0001540734,0.0002067769,0.0001812566,0.0002442361,0.0001802857,0.0003893933,0.0003823597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002161088,"about_ca_system_score_gemma":0.0004013593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001301896,"about_ca_topic_score_gemma":0.001231773,"domain_scores_codex":[0.9998287,0.0000249413,0.00001042391,0.00003175986,0.00008393889,0.00002031542],"domain_scores_gemma":[0.9998394,0.00004342252,0.00002488645,0.00002453466,0.00006004596,0.000007556901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008556716,0.0004253507,0.003281616,0.0007471413,0.0001003145,0.0004396906,0.0002913541,0.1705934,0.2161583,0.01286377,0.005118235,0.589125],"study_design_scores_gemma":[0.00008973267,0.0007323285,0.001635084,0.00003531212,0.00004894884,0.000242065,0.00002574228,0.9251429,0.06423535,0.0008909972,0.006896561,0.0000249332],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07452453,0.0004768251,0.9091086,0.0002500676,0.0002072632,0.000174566,0.00005843807,0.003266727,0.01193304],"genre_scores_gemma":[0.9486327,0.00009406973,0.04908572,0.00003773295,0.00003002048,0.00007962988,0.00004243045,0.00002252407,0.001975309],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001891866,"threshold_uncertainty_score":0.006328881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006563025886897178,"score_gpt":0.2059405836715572,"score_spread":0.19937755778466,"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."}}