{"id":"W4391019820","doi":"10.1109/cdc49753.2023.10383832","title":"Data-Driven Output Regulation Using Single-Gain Tuning Regulators","year":2023,"lang":"en","type":"article","venue":"","topic":"Adaptive Dynamic Programming Control","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Control theory (sociology); Regulator; Computer science; MIMO; Control engineering; Convex optimization; Scalar (mathematics); Controller (irrigation); Linear system; Regular polygon; Engineering; Control (management); Mathematics; Channel (broadcasting)","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":[0.0009131234,0.0004755165,0.0006377797,0.0003163543,0.0002942291,0.001015631,0.0008835088,0.0007088366,0.001178917],"category_scores_gemma":[0.002792648,0.0002946277,0.000386871,0.0003542646,0.0008418515,0.0008062787,0.0009377251,0.001048482,0.0004835833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003934694,"about_ca_system_score_gemma":0.000427619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005074791,"about_ca_topic_score_gemma":0.0004181881,"domain_scores_codex":[0.9991663,0.0001397786,0.00003997673,0.0002447769,0.0003523587,0.00005688105],"domain_scores_gemma":[0.9991589,0.0004066947,0.0001276887,0.0001246838,0.0001631868,0.00001888367],"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":[0.0003086611,0.0001545475,0.0006204161,0.0004315671,0.00006822623,0.0001491792,0.0003127845,0.5107975,0.1656979,0.08269288,0.002469572,0.2362967],"study_design_scores_gemma":[0.00002374014,0.0001360371,0.0001253099,0.00002681382,0.0000114223,0.00004960486,0.00001109369,0.9627762,0.02118036,0.0114563,0.004177025,0.00002601647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005322685,0.0001470966,0.9913696,0.00006846208,0.00003439287,0.00002136009,0.00001041553,0.0003549063,0.00267107],"genre_scores_gemma":[0.840297,0.0003602594,0.1552394,0.0002127798,0.00007503157,0.0001662305,0.00004668044,0.0001089931,0.003493569],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001178917,"threshold_uncertainty_score":0.004829168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09231915592367608,"score_gpt":0.2936539176518024,"score_spread":0.2013347617281263,"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."}}