{"id":"W189026918","doi":"","title":"LINEAR AND NONLINEAR MODEL PREDICTIVE CONTROL DESIGN FOR A MILK PASTEURIZATION PLANT","year":2003,"lang":"en","type":"article","venue":"Control and Intelligent Systems","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Model predictive control; Control theory (sociology); Benchmark (surveying); PID controller; Nonlinear system; Artificial neural network; Linear model; Controller (irrigation); Operating point; Nonlinear model; Smith predictor; Control engineering; Engineering; Computer science; Temperature control; Control (management); Artificial intelligence; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006885867,0.0006009369,0.0005024825,0.0001804303,0.0005147679,0.0007971947,0.0005882114,0.000766738,0.001588082],"category_scores_gemma":[0.0009101341,0.0003650504,0.0003247973,0.0001744933,0.0005277648,0.0004498458,0.000489323,0.0008222245,0.0003371959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006298273,"about_ca_system_score_gemma":0.0009559983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00571598,"about_ca_topic_score_gemma":0.004950029,"domain_scores_codex":[0.9997446,0.00005894393,0.00001054493,0.00005847306,0.0001047677,0.00002274692],"domain_scores_gemma":[0.9996837,0.0001195906,0.00006262468,0.00001677889,0.0001071607,0.0000100745],"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":[0.00008349197,0.00003712177,0.0002174533,0.0001561063,0.00001700843,0.00006501369,0.00006246929,0.9634535,0.007860797,0.003020622,0.0003693542,0.02465704],"study_design_scores_gemma":[0.00001018045,0.00007589348,0.0001213791,0.000004742284,0.000007341001,0.000007296165,0.000006427063,0.9973956,0.001329466,0.000563403,0.0004743871,0.000003869022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03945358,0.0007987732,0.9488822,0.000378076,0.00007717578,0.0001047719,0.00004823029,0.0003886173,0.00986861],"genre_scores_gemma":[0.9457741,0.0004312412,0.04834591,0.0000835004,0.0000476175,0.0001947811,0.00005944058,0.00002342563,0.005039904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00571598,"threshold_uncertainty_score":0.01136541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01526936733743735,"score_gpt":0.2098473493727142,"score_spread":0.1945779820352769,"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."}}