{"id":"W2127850730","doi":"10.1109/ias.2005.1518524","title":"Model reference adaptive flux observer based neuro-fuzzy controller for induction motor drive","year":2005,"lang":"en","type":"article","venue":"Fourtieth IAS Annual Meeting. Conference Record of the 2005 Industry Applications Conference, 2005.","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Control theory (sociology); Observer (physics); Computer science; Flux linkage; Induction motor; Controller (irrigation); Reference model; Fuzzy logic; PID controller; Control engineering; Voltage; Engineering; Direct torque control; Artificial intelligence; Temperature control; Control (management); Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006467169,0.0007856773,0.0009410815,0.0003422398,0.000328451,0.0001175819,0.001447705,0.00108085,0.0002637718],"category_scores_gemma":[0.0003694835,0.0006933226,0.0003331063,0.0006163131,0.0003234996,0.0004950142,0.0001166746,0.001734146,0.00006252128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003607313,"about_ca_system_score_gemma":0.0008270457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001059397,"about_ca_topic_score_gemma":0.0002585328,"domain_scores_codex":[0.995747,0.0002040492,0.001332545,0.0008708573,0.0006393792,0.001206145],"domain_scores_gemma":[0.9955149,0.0006388978,0.0007504189,0.001121535,0.001572083,0.0004021295],"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":[0.001338455,0.0008880548,0.001279718,0.0002793279,0.0008062719,0.000001530811,0.0008111548,0.6039393,0.04067642,0.03083662,0.05755609,0.261587],"study_design_scores_gemma":[0.001908779,0.0001743344,0.001047349,0.000195644,0.0002239279,0.000004818519,0.0003402459,0.9340292,0.005724709,0.001975744,0.05356898,0.0008062332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2810047,0.0007110007,0.64186,0.009947663,0.001644036,0.01644574,0.004089597,0.001874079,0.04242318],"genre_scores_gemma":[0.9683902,0.00006429575,0.02479913,0.000342124,0.0005826122,0.00213992,0.00006050498,0.000119366,0.003501883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6873854,"threshold_uncertainty_score":0.9995518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04152735775879834,"score_gpt":0.2498740817777538,"score_spread":0.2083467240189555,"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."}}