{"id":"W2085545871","doi":"10.1016/j.jprocont.2011.12.014","title":"An auto-tuning method for dominant-pole placement using implicit model reference adaptive control technique","year":2012,"lang":"en","type":"article","venue":"Journal of Process Control","topic":"Advanced Control Systems Design","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Control theory (sociology); Reference model; Full state feedback; Auto tuning; Computer science; Scheme (mathematics); Control engineering; Control (management); Mathematics; Engineering; Artificial intelligence; PID controller","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"],"consensus_categories":[],"category_scores_codex":[0.001738715,0.0003546118,0.000898026,0.0002410352,0.0001154238,0.0000526515,0.0003867562,0.0001945942,0.000005857307],"category_scores_gemma":[0.0001478252,0.0003094867,0.0001530493,0.000158386,0.0000236834,0.00123966,0.000009041266,0.0004361274,0.000001225981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003864238,"about_ca_system_score_gemma":0.0001748528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005238365,"about_ca_topic_score_gemma":0.000001753564,"domain_scores_codex":[0.9976327,0.000143452,0.0009589237,0.0001905143,0.0003604034,0.0007139982],"domain_scores_gemma":[0.9976954,0.0003317656,0.0006750281,0.000247612,0.0007300926,0.0003201018],"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":[0.0005503456,0.00004215314,0.00004086087,0.00007611686,0.0001598843,0.000002569404,0.0002704789,0.5638314,0.4326652,0.0005378199,0.00001577448,0.00180739],"study_design_scores_gemma":[0.005527577,0.0003621844,0.00001448843,0.0001876757,0.0002720204,0.000159829,0.0003078255,0.9766389,0.01487081,0.00114791,0.0001707638,0.0003400829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002327932,0.001225762,0.994624,0.00002582395,0.0002114707,0.001331698,0.00004890266,0.00009333444,0.0001111399],"genre_scores_gemma":[0.8278629,0.000005300016,0.1712986,0.00007014258,0.0004246364,0.0002481464,8.28981e-7,0.00007847142,0.00001102042],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8255349,"threshold_uncertainty_score":0.9999357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03632510397042764,"score_gpt":0.331252788667256,"score_spread":0.2949276846968283,"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."}}