{"id":"W3215218948","doi":"10.1109/epec52095.2021.9621734","title":"Dynamic Performance Improvement of Brushless DC Motors Using a Hybrid MTPV/MTPA Control","year":2021,"lang":"en","type":"article","venue":"","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Control theory (sociology); Torque; Computer science; Steady state (chemistry); Controller (irrigation); Exploit; DC motor; Direct torque control; Control (management); Voltage; Control engineering; Engineering; Induction motor; Physics; 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":[0.0002058839,0.0004428181,0.0003575641,0.0003311801,0.0002118003,0.0005004685,0.0004029282,0.000325052,0.001130177],"category_scores_gemma":[0.0002972692,0.0001369249,0.0001798396,0.0002351268,0.0001594036,0.0004010058,0.0002762798,0.0002821632,0.0002982151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001468438,"about_ca_system_score_gemma":0.0001074366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004131666,"about_ca_topic_score_gemma":0.0005212894,"domain_scores_codex":[0.9997814,0.00002497044,0.00001480213,0.00004308289,0.0001203737,0.00001535443],"domain_scores_gemma":[0.9998479,0.00003447179,0.00002925555,0.00002045179,0.00005874002,0.000009241987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004789198,0.0001450038,0.0009681485,0.0003283127,0.00005332058,0.0001772331,0.0001301744,0.02770627,0.6944925,0.002449693,0.001234461,0.271836],"study_design_scores_gemma":[0.00009939011,0.001406813,0.004810732,0.00004837771,0.000059003,0.0004821965,0.00004704775,0.7173805,0.261823,0.0007716159,0.01302507,0.00004627808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.254898,0.001778448,0.726749,0.0001904345,0.0001516921,0.00008598185,0.00005364171,0.001653901,0.01443892],"genre_scores_gemma":[0.9774796,0.0001935315,0.02042718,0.00002671342,0.00002050453,0.00002910548,0.00002810985,0.00002073076,0.00177447],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001130177,"threshold_uncertainty_score":0.003780782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005323613464407434,"score_gpt":0.1931043972562521,"score_spread":0.1877807837918447,"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."}}