{"id":"W2558658794","doi":"10.1002/asjc.1305","title":"A Receding Horizon Sliding Controller for Automotive Engine Coldstart: Design and Hardware‐in‐the‐Loop Testing With an Echo State Network High‐Fidelity Model","year":2016,"lang":"en","type":"article","venue":"Asian Journal of Control","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Control theory (sociology); Model predictive control; Controller (irrigation); SPARK (programming language); Optimal control; Engineering; Control engineering; Hardware-in-the-loop simulation; High fidelity; Computer science; Control (management); Mathematical optimization; Mathematics","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":[0.003297915,0.0002382127,0.0005240099,0.0001166046,0.0002803314,0.0002896434,0.0006882779,0.00005697829,4.42293e-7],"category_scores_gemma":[0.000329135,0.0001254509,0.00008229858,0.0003246118,0.00004185314,0.0009350709,0.00005090684,0.000294413,2.339099e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006205519,"about_ca_system_score_gemma":0.0001439789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000368613,"about_ca_topic_score_gemma":0.000007255871,"domain_scores_codex":[0.9976742,0.000401262,0.0006386035,0.0003246307,0.0003452665,0.0006160613],"domain_scores_gemma":[0.9966408,0.001766185,0.0006096948,0.0002258769,0.000557263,0.0002001882],"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":[0.0009608598,0.00005900977,0.0008989042,0.00001599258,0.0001207602,0.0001427189,0.0007005458,0.7723876,0.001308071,0.001581826,0.0002767982,0.2215469],"study_design_scores_gemma":[0.005841835,0.002339075,0.0007069745,0.0004639962,0.00003644299,0.0001602709,0.00004970494,0.9801328,0.00009017548,0.009949046,0.00002755484,0.0002021063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04145254,0.0001871175,0.9535297,0.00397881,0.0001744981,0.0006201191,0.000002383314,0.00003518301,0.00001965069],"genre_scores_gemma":[0.8305336,0.00001012729,0.1687721,0.0002590231,0.0003820627,0.00001351984,1.036469e-7,0.00001732228,0.0000121761],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.789081,"threshold_uncertainty_score":0.5115741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02383999244386958,"score_gpt":0.2353165603911949,"score_spread":0.2114765679473254,"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."}}