{"id":"W62883389","doi":"","title":"Neural networks and neuro-fuzzy based states and parameters estimation in induction motor sensorless drive","year":2005,"lang":"en","type":"article","venue":"ACMOS'05 Proceedings of the 7th WSEAS international conference on Automatic control, modeling and simulation","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Induction motor; Control theory (sociology); Artificial neural network; Vector control; Control engineering; Kalman filter; Rotor (electric); Extended Kalman filter; Computer science; Field (mathematics); Neuro-fuzzy; Fuzzy logic; Engineering; Artificial intelligence; Fuzzy control system; Control (management); Mathematics","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":[0.0004919058,0.000290552,0.0003792934,0.0002953725,0.0001737738,0.0005991814,0.0004094894,0.0006491062,0.0006251697],"category_scores_gemma":[0.001452249,0.0001989127,0.0002218325,0.0004120329,0.0003893983,0.0007240746,0.0002279989,0.0004702525,0.0001330954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004347675,"about_ca_system_score_gemma":0.0002660298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00588164,"about_ca_topic_score_gemma":0.003513471,"domain_scores_codex":[0.9997903,0.00006150483,0.00001730789,0.0000351261,0.00008129313,0.00001457297],"domain_scores_gemma":[0.9997681,0.0001221607,0.00003123601,0.00001384916,0.00005878986,0.000005930423],"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":[0.0001430814,0.00004096459,0.0007075337,0.000118376,0.00003534205,0.0001044863,0.00008011991,0.8475645,0.003536328,0.01717925,0.0008593735,0.1296307],"study_design_scores_gemma":[0.000002732549,0.00001330156,0.0002733219,0.000007335339,0.000004122399,0.00001125361,0.000005345598,0.9952443,0.0006060361,0.003369268,0.0004575596,0.000005443259],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05082244,0.006800361,0.9330012,0.0005742455,0.0002136901,0.00003730116,0.00006876697,0.0003436785,0.008138378],"genre_scores_gemma":[0.9467477,0.002424892,0.04590962,0.00007751129,0.0001025232,0.0000601639,0.00005407591,0.00001720446,0.004606363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00588164,"threshold_uncertainty_score":0.01169479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01779819924603583,"score_gpt":0.2457119547528243,"score_spread":0.2279137555067885,"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."}}