{"id":"W4310970676","doi":"10.1109/iecon49645.2022.9968728","title":"Enhanced Adaptive Higher Order Sliding Mode Observer based Sensorless Control","year":2022,"lang":"en","type":"article","venue":"IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society","topic":"Sensorless Control of Electric Motors","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Control theory (sociology); Observer (physics); Fuzzy logic; Sliding mode control; Computer science; State observer; Variable (mathematics); Adaptive control; Mode (computer interface); Fuzzy control system; Control engineering; Control (management); Mathematics; Engineering; Nonlinear system; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003276046,0.0003525986,0.0004777386,0.0002738517,0.0001522213,0.0004665189,0.0006446003,0.0003640795,0.001137369],"category_scores_gemma":[0.0006091615,0.0001483958,0.000333207,0.000192336,0.0002316928,0.0005469694,0.0003211238,0.0005524123,0.0001631939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002388369,"about_ca_system_score_gemma":0.0002909165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001546844,"about_ca_topic_score_gemma":0.001514364,"domain_scores_codex":[0.9997009,0.00004095152,0.00002045446,0.00005818959,0.0001558897,0.00002365005],"domain_scores_gemma":[0.9997213,0.0000778153,0.00003604378,0.0000346474,0.0001190689,0.00001112816],"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":[0.0005336724,0.0001614891,0.002130965,0.0004845346,0.0001163198,0.0003093519,0.000355812,0.3230987,0.2206567,0.01913304,0.002429188,0.4305903],"study_design_scores_gemma":[0.00002777083,0.0001677635,0.0009649757,0.000007989765,0.00001483886,0.00006315625,0.00001125929,0.9791942,0.01639996,0.0008902923,0.0022436,0.00001420029],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02419836,0.0002641623,0.9723117,0.00005176965,0.00008631834,0.00003056904,0.00001850575,0.0006129544,0.002425526],"genre_scores_gemma":[0.9389871,0.0002390551,0.05648175,0.00004768858,0.00003728874,0.00005390709,0.00005866892,0.00002145835,0.00407317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001546844,"threshold_uncertainty_score":0.003804922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03168146302650286,"score_gpt":0.2230081478117333,"score_spread":0.1913266847852305,"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."}}