{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0007142561,0.0005564901,0.0008354666,0.00009598639,0.000493893,0.00007366674,0.001198412,0.0003797734,0.0006584973],"category_scores_gemma":[0.0001218943,0.0005341092,0.0006285885,0.001097859,0.0001315033,0.0002677829,0.0001138558,0.002442244,0.000006086298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001185355,"about_ca_system_score_gemma":0.001295446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001633871,"about_ca_topic_score_gemma":0.00005105442,"domain_scores_codex":[0.9959792,0.0004724184,0.0007847086,0.0005793467,0.0009919332,0.00119239],"domain_scores_gemma":[0.9977874,0.0004173608,0.0004164868,0.0007084004,0.0005007064,0.0001696607],"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":[0.0006760611,0.0002371858,0.00009836962,0.00004459313,0.001181246,0.000005791448,0.001445462,0.7966883,0.1696588,0.003524296,0.02224547,0.004194436],"study_design_scores_gemma":[0.0138965,0.0009004387,0.0001144676,0.00006481546,0.0004037412,0.000008053712,0.001682695,0.7999558,0.1677803,0.0006773841,0.0130246,0.001491123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9793275,0.0008665686,0.008641052,0.001181026,0.005120276,0.001952664,0.0009792382,0.0004566734,0.001474977],"genre_scores_gemma":[0.997625,0.00003978403,0.00009988086,0.0004371762,0.0004431374,0.0002189752,0.00002215088,0.0001095061,0.001004415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01829745,"threshold_uncertainty_score":0.9998592,"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."}}