{"id":"W4313644954","doi":"10.1016/j.ins.2022.12.115","title":"Data-driven set-point control for nonlinear nonaffine systems","year":2023,"lang":"en","type":"article","venue":"Information Sciences","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Control theory (sociology); Controller (irrigation); Nonlinear system; Computer science; Feedback linearization; Parametric statistics; Convergence (economics); Nonlinear control; Linearization; Mathematics; Control (management); 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":[0.0006437357,0.00009482218,0.0001469692,0.000208107,0.0001509554,0.0001979715,0.0004080317,0.00004223084,0.000004405581],"category_scores_gemma":[0.000178704,0.00008257107,0.00002166275,0.0005512593,0.00004077411,0.003219485,0.00003425801,0.00003946634,0.0002631828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000350185,"about_ca_system_score_gemma":0.00003274146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001118864,"about_ca_topic_score_gemma":0.000009409242,"domain_scores_codex":[0.9989796,0.00001125557,0.0004109647,0.0001052604,0.0002647655,0.0002281154],"domain_scores_gemma":[0.9993342,0.0001586656,0.00009965117,0.0002454424,0.0001172563,0.00004484878],"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":[0.000002754207,7.970125e-7,0.00002975864,0.00004827686,0.000008153997,1.037421e-7,0.0001395094,0.9927539,0.00004597006,0.0004709396,0.004557496,0.001942303],"study_design_scores_gemma":[0.0004637674,0.00002049278,0.00004921127,0.00001794049,0.000004852598,0.000002443234,0.0003687405,0.9269498,0.0000144382,0.00002964566,0.07198147,0.00009721739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001900163,0.00006239492,0.9924695,0.0001877366,0.001147157,0.0008085596,0.0009759822,0.0008420448,0.001606462],"genre_scores_gemma":[0.9899584,0.00002714089,0.008423775,0.0001022138,0.0002520095,0.0002091535,0.0009261419,0.00001379916,0.00008736891],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9880582,"threshold_uncertainty_score":0.338277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03758642766272343,"score_gpt":0.2873254562412145,"score_spread":0.249739028578491,"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."}}