{"id":"W2168509965","doi":"10.1109/ccece.2006.277854","title":"Nonlinear Control of Interior Permanent Magnet Synchronous Motor Incorporating Flux Control","year":2006,"lang":"en","type":"article","venue":"","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Backstepping; Robustness (evolution); Control theory (sociology); Torque; Nonlinear system; Electronic speed control; MATLAB; Control engineering; Computer science; Vector control; Direct torque control; Robust control; Controller (irrigation); Adaptive control; Engineering; Induction motor; Control (management); Voltage; Physics; Artificial intelligence; 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":[0.0002115248,0.000312849,0.000241441,0.000120339,0.0001599851,0.0003280959,0.0003746426,0.0002529356,0.001206083],"category_scores_gemma":[0.0003833599,0.00008651343,0.0001631505,0.00009754122,0.0003068876,0.0002911018,0.0002448378,0.0002964434,0.0002904155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001674446,"about_ca_system_score_gemma":0.0001864402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007817702,"about_ca_topic_score_gemma":0.0009588553,"domain_scores_codex":[0.9998841,0.00002285345,0.000007277054,0.00002197166,0.00005556367,0.000008272827],"domain_scores_gemma":[0.9998703,0.00003926234,0.0000234946,0.00001227643,0.00004854054,0.000006106749],"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":[0.0004651168,0.0001809326,0.001009318,0.0009461486,0.00004493623,0.0003964952,0.0003541992,0.3991653,0.2738489,0.0185525,0.002148694,0.3028874],"study_design_scores_gemma":[0.00003222267,0.0004172515,0.0007742514,0.00001378769,0.00001421844,0.0000735334,0.00001482167,0.976157,0.01663951,0.001175027,0.004678362,0.00001011434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0873567,0.0003981,0.8971816,0.0001333907,0.0001535621,0.00006280508,0.00003560426,0.000745863,0.0139324],"genre_scores_gemma":[0.950089,0.0002180012,0.04374319,0.00003314702,0.00004719708,0.00004934301,0.00003321056,0.00002154264,0.00576548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001206083,"threshold_uncertainty_score":0.004034698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003300990091977722,"score_gpt":0.1799101505691213,"score_spread":0.1766091604771436,"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."}}