{"id":"W1480774276","doi":"10.1109/taes.2014.130766","title":"Enhanced adaptive unscented Kalman filter for reaction wheels","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Kalman filter; Control theory (sociology); Particle swarm optimization; Extended Kalman filter; Computer science; Fault detection and isolation; Unscented transform; Fast Kalman filter; Actuator; Engineering; Control engineering; Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002233352,0.0002384257,0.00029354,0.0001221975,0.0001278667,0.0000652119,0.00006937068,0.0001596082,0.000003838881],"category_scores_gemma":[0.000003231077,0.0002330672,0.00009686909,0.0001837534,0.00002155631,0.000147197,3.279234e-7,0.0002545186,0.00004560651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003835029,"about_ca_system_score_gemma":0.0000477865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001647033,"about_ca_topic_score_gemma":0.000389851,"domain_scores_codex":[0.998764,0.00005370157,0.0002592421,0.0002710388,0.0001827658,0.0004692246],"domain_scores_gemma":[0.999433,0.00005428998,0.00005067225,0.0002095348,0.00008728148,0.0001651965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001866299,0.0002899559,0.000005853734,0.0004553991,0.001344557,0.000003790203,0.003128542,0.3399385,0.6152865,0.001411395,0.008733856,0.0275354],"study_design_scores_gemma":[0.008216281,0.002543025,0.00001866316,0.0003172916,0.0002196681,0.0001314722,0.004373652,0.7492419,0.1655688,0.00009689463,0.06809151,0.001180793],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08475202,0.001064124,0.9085403,0.0000910797,0.00277587,0.001113619,0.00002888761,0.0005404992,0.001093571],"genre_scores_gemma":[0.9965226,0.0001342433,0.0000178096,0.00002802554,0.0001637578,0.0005480594,0.000003222257,0.00005278015,0.00252949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9117706,"threshold_uncertainty_score":0.9504206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01511586832493313,"score_gpt":0.2229383799623595,"score_spread":0.2078225116374264,"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."}}