{"id":"W3129776981","doi":"10.1109/icjece.2020.3018495","title":"Effective Model Predictive Voltage Control for a Sensorless Doubly Fed Induction Generator","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Multilevel Inverters and Converters","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Model predictive control; Control theory (sociology); Doubly fed electric machine; Generator (circuit theory); Voltage; Induction generator; Control (management); Computer science; Engineering; Physics; AC power; Electrical engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002274778,0.000381827,0.0003272378,0.0001662764,0.0001971617,0.0005430655,0.000587553,0.0003107032,0.0006990026],"category_scores_gemma":[0.0003882642,0.0001355813,0.0001781014,0.0002068435,0.0002655663,0.0003985336,0.0002447608,0.0005422669,0.0001265577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002484846,"about_ca_system_score_gemma":0.0002731408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001240637,"about_ca_topic_score_gemma":0.001611488,"domain_scores_codex":[0.9998264,0.00003250012,0.000007776809,0.00002797141,0.00009367432,0.0000117652],"domain_scores_gemma":[0.9998862,0.0000417613,0.00002473306,0.00001445898,0.00002796565,0.000004895891],"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":[0.0002589318,0.0001148571,0.0005963164,0.0003417447,0.00006371277,0.0003149062,0.0001495075,0.6868356,0.05053251,0.01975082,0.002077383,0.2389637],"study_design_scores_gemma":[0.0000101799,0.0001033908,0.0001239012,0.000005891743,0.000006812014,0.0000259751,0.00000379879,0.994432,0.003321757,0.0009989496,0.0009628579,0.00000437087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03259118,0.0004440432,0.9620289,0.0001418134,0.00009969362,0.0000294084,0.00003410432,0.0004754022,0.00415551],"genre_scores_gemma":[0.977266,0.0001500644,0.02144274,0.00002778802,0.00001990678,0.00002875873,0.00002552595,0.00001053942,0.001028731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001240637,"threshold_uncertainty_score":0.002466798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006340788586720623,"score_gpt":0.1683699226931379,"score_spread":0.1620291341064172,"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."}}