{"id":"W2480967224","doi":"10.1109/iecon.1994.398145","title":"Adaptive nonlinear control of a permanent magnet synchronous motor","year":2002,"lang":"en","type":"article","venue":"","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Control theory (sociology); Decoupling (probability); Feedback linearization; Nonlinear system; A priori and a posteriori; Adaptive control; Linearization; Torque; Permanent magnet synchronous motor; Vector control; Computer science; Magnet; Control engineering; Control (management); Engineering; Induction motor; Artificial intelligence; Physics; Voltage; Electrical engineering","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":[0.0001066152,0.0002063483,0.0001247008,0.00008409157,0.0001508741,0.0001961215,0.0002446036,0.000187494,0.0008744652],"category_scores_gemma":[0.0002686047,0.00005878563,0.0001105768,0.00007417053,0.0002349516,0.0001522834,0.0001666811,0.0001978681,0.0001756953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001636915,"about_ca_system_score_gemma":0.0001506429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001331739,"about_ca_topic_score_gemma":0.001367121,"domain_scores_codex":[0.9999382,0.00001114564,0.000002562718,0.00001473241,0.00002806179,0.000005405526],"domain_scores_gemma":[0.9999325,0.0000205239,0.00001247132,0.000005721157,0.00002410166,0.000004613866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002439903,0.00007417323,0.0007885756,0.000297598,0.00003512699,0.0002918284,0.0002377736,0.466322,0.2062235,0.01415527,0.00201147,0.3093186],"study_design_scores_gemma":[0.00001751123,0.0001808097,0.0005730577,0.000005199088,0.000007227421,0.00005276655,0.00001042079,0.9838668,0.009600393,0.001175428,0.004502041,0.000008402285],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08588758,0.0003974296,0.9024734,0.0001803671,0.0001592456,0.00003966558,0.00001845738,0.0005550152,0.0102888],"genre_scores_gemma":[0.9648663,0.0001809547,0.02848858,0.00003572825,0.00004072352,0.00003273363,0.00001482764,0.00001268744,0.006327472],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001331739,"threshold_uncertainty_score":0.002925336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007706289519242176,"score_gpt":0.1735126638141857,"score_spread":0.1658063742949435,"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."}}