{"id":"W3099995860","doi":"10.1109/pedg48541.2020.9244307","title":"Modulated Model Predictive Torque and Power Control of Gearless PMSG Wind Turbines","year":2020,"lang":"en","type":"article","venue":"","topic":"Multilevel Inverters and Converters","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada; Connecticut State Emergency Response Commission","keywords":"Control theory (sociology); Permanent magnet synchronous generator; Wind power; Torque; Duty cycle; Turbine; Model predictive control; Transient (computer programming); Converters; AC power; Voltage; Grid; Power (physics); Computer science; Generator (circuit theory); Direct torque control; Engineering; Control (management); Electrical engineering; Physics; Mathematics; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001986019,0.0003463568,0.0002859004,0.0001754337,0.0001507073,0.0003660924,0.0004748029,0.0002674119,0.0008384558],"category_scores_gemma":[0.0004603796,0.0001261192,0.0001437318,0.0002050996,0.0002287403,0.0003640212,0.0001556257,0.0003326864,0.0001630855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001474897,"about_ca_system_score_gemma":0.0001449305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007349096,"about_ca_topic_score_gemma":0.0009667165,"domain_scores_codex":[0.9998882,0.00002440433,0.000006452059,0.0000195882,0.0000520972,0.000009232977],"domain_scores_gemma":[0.9998853,0.00003582835,0.00002968179,0.00001522553,0.00002993206,0.000004068595],"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":[0.0002752212,0.0001185903,0.0008356565,0.0004157054,0.00005307264,0.0002625334,0.000158605,0.655148,0.04959034,0.02185292,0.002522638,0.2687667],"study_design_scores_gemma":[0.0000193977,0.0001015622,0.0002991566,0.000007020695,0.000006659649,0.00003032369,0.000006349617,0.9919544,0.004286027,0.001934118,0.001350492,0.000004516771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07620622,0.001011079,0.9126989,0.0001841238,0.0002199911,0.00006734325,0.00006154116,0.0006043033,0.008946483],"genre_scores_gemma":[0.9831541,0.0001660566,0.01541913,0.0000254556,0.000020689,0.00002838109,0.0000253677,0.00001130127,0.001149375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008384558,"threshold_uncertainty_score":0.002804935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009739681635520137,"score_gpt":0.1801106073034103,"score_spread":0.1703709256678902,"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."}}