{"id":"W1833607760","doi":"10.1109/iecon.2001.975988","title":"Speed control of induction motors using a nonlinear auto-disturbance rejection controller","year":2002,"lang":"en","type":"article","venue":"","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Control theory (sociology); Overshoot (microwave communication); Induction motor; Controller (irrigation); Nonlinear system; Disturbance (geology); Electronic speed control; Computer science; Robust control; Control engineering; Steady state (chemistry); Operating point; Engineering; Control system; Control (management); Electronic engineering; Artificial intelligence","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":[0.0003030026,0.0004052457,0.0002854877,0.0001992517,0.000163937,0.0004527254,0.0005556915,0.0002948371,0.0008163078],"category_scores_gemma":[0.0006473529,0.0001177932,0.0001811927,0.0001243831,0.0002118183,0.0002798967,0.0001993019,0.0003971605,0.0005918688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001931454,"about_ca_system_score_gemma":0.0001729626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001090479,"about_ca_topic_score_gemma":0.0009218318,"domain_scores_codex":[0.9997227,0.00002901384,0.00001910952,0.00005234134,0.0001586205,0.00001829637],"domain_scores_gemma":[0.9997242,0.00006036261,0.00006337553,0.00003048146,0.0001105484,0.00001096666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004330392,0.0001541724,0.00118762,0.00058481,0.00007302743,0.0003135111,0.0001597323,0.09789226,0.3686123,0.003115986,0.002498304,0.5249751],"study_design_scores_gemma":[0.0001313707,0.0008556045,0.003235291,0.00002555036,0.00007630437,0.0004694152,0.00001805291,0.870211,0.1086065,0.0007899785,0.01554224,0.00003865937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05124066,0.0007621812,0.9399784,0.000115776,0.0001334407,0.00006435759,0.00004410028,0.002519074,0.005141972],"genre_scores_gemma":[0.9167071,0.0004967685,0.07667184,0.00006470638,0.0001068159,0.00006004931,0.0001226247,0.00009393306,0.005676189],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001090479,"threshold_uncertainty_score":0.002730846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0173417265001197,"score_gpt":0.2063135468550579,"score_spread":0.1889718203549382,"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."}}