{"id":"W1984103751","doi":"10.3182/20070606-3-mx-2915.00120","title":"PERFORMANCE-DRIVEN ADAPTIVE PID CONTROLLER DESIGN : THEORY AND EXPERIMENTAL EVALUATION","year":2007,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"PID controller; Control theory (sociology); Control engineering; Controller (irrigation); Limit (mathematics); Identification (biology); Process (computing); Engineering; System identification; Scheme (mathematics); Adaptive control; Identification scheme; Computer science; Control (management); Temperature control; Data modeling; Mathematics; 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":[0.001128076,0.0001627053,0.0001804809,0.0001093213,0.0001114853,0.00005872471,0.00006794641,0.00008858208,0.00004962967],"category_scores_gemma":[0.00003909484,0.0001533565,0.00003653123,0.0001055408,0.00004345422,0.0002988725,0.00001351968,0.0001082321,0.00003508101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001291024,"about_ca_system_score_gemma":0.000009824567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000445693,"about_ca_topic_score_gemma":0.00000115519,"domain_scores_codex":[0.9990797,0.00001688917,0.0002147717,0.0001805412,0.0002552443,0.0002528246],"domain_scores_gemma":[0.9996713,0.00005430097,0.00004400152,0.00004105276,0.0001050264,0.0000842634],"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":[0.002654171,0.0001162538,0.008063497,0.0001723854,0.0005798978,0.000003607763,0.01707546,0.0146765,0.6921357,0.002739802,0.003115697,0.2586671],"study_design_scores_gemma":[0.001721404,0.0002316933,0.003254319,0.00003760585,0.00003595179,0.00001822278,0.003022947,0.9407063,0.04975622,0.00009497185,0.0008818713,0.0002385554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9794215,0.001389219,0.00728502,0.00000796179,0.0002986038,0.000682499,0.000001091845,0.0003477593,0.01056635],"genre_scores_gemma":[0.9990314,0.00001289995,0.000382746,0.00002812343,0.0001662052,0.0001182467,5.829564e-7,0.00002815973,0.0002316009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9260297,"threshold_uncertainty_score":0.6253696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01563333085044323,"score_gpt":0.2387714258039187,"score_spread":0.2231380949534755,"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."}}