{"id":"W2020360925","doi":"10.1109/ias.2010.5614101","title":"Performance Analysis of an FLC Based Online Adaptation of Both Hysteresis and PI Controllers for IPMSM Drive","year":2010,"lang":"en","type":"article","venue":"","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Control theory (sociology); Torque; Torque ripple; Controller (irrigation); Electronic speed control; Vector control; PID controller; Computer science; Direct torque control; Motor drive; Ripple; Pulse-width modulation; Voltage; Control engineering; Engineering; Induction motor; Physics; Control (management); 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":[0.0006541656,0.0005122899,0.0004422636,0.0002859394,0.0003387178,0.0005339032,0.0005713642,0.0006324421,0.002081885],"category_scores_gemma":[0.001420429,0.0001656924,0.0002200083,0.0001389377,0.0002744806,0.0003781488,0.0002276023,0.0005419551,0.0003045332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004567733,"about_ca_system_score_gemma":0.0003580702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002197951,"about_ca_topic_score_gemma":0.001557377,"domain_scores_codex":[0.9995292,0.00007192022,0.0000323834,0.00007169861,0.0002465814,0.00004824399],"domain_scores_gemma":[0.9993075,0.0003021618,0.00007119469,0.00006293194,0.000237625,0.00001845204],"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":[0.001557963,0.0004216658,0.003502133,0.0008656902,0.0001940942,0.0004154425,0.0003235454,0.4388589,0.1466249,0.005187897,0.001665938,0.4003817],"study_design_scores_gemma":[0.00003622392,0.0006506764,0.00150552,0.00001029674,0.00002921934,0.00008394239,0.00001434529,0.9738056,0.02265067,0.0002395501,0.0009619656,0.00001203622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.242255,0.0007259818,0.7450134,0.0001929568,0.0001073426,0.0001487303,0.00005536584,0.001625645,0.009875674],"genre_scores_gemma":[0.9864434,0.0000670964,0.0123129,0.00002695906,0.00000928464,0.00004140108,0.00002964038,0.00001396041,0.001055225],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002197951,"threshold_uncertainty_score":0.006964564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009174883307734005,"score_gpt":0.213846664526565,"score_spread":0.204671781218831,"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."}}