{"id":"W1748824602","doi":"10.1002/cjce.22227","title":"Constrained model predictive control with economic optimization for integrating process","year":2015,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Services Fédéraux des Affaires Scientifiques, Techniques et Culturelles; National Natural Science Foundation of China","keywords":"Steady state (chemistry); Process (computing); Mathematical optimization; Optimal control; State variable; Control theory (sociology); Constraint (computer-aided design); Computer science; Model predictive control; Optimization problem; Quadratic programming; State (computer science); Dynamic programming; Control variable; Quadratic equation; Control (management); Mathematics; Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001940676,0.0001288419,0.0002070136,0.00008415576,0.00002936518,0.00004373308,0.0001539909,0.00006108304,0.000001777322],"category_scores_gemma":[0.0001679085,0.00009732657,0.0000383108,0.00006296684,0.00003307761,0.0002237737,0.0000015205,0.000178261,2.579618e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004903217,"about_ca_system_score_gemma":0.0004865683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002703408,"about_ca_topic_score_gemma":0.00006117452,"domain_scores_codex":[0.999356,0.000004977899,0.0002815313,0.00006352714,0.00008128749,0.0002126965],"domain_scores_gemma":[0.9992465,0.00006540168,0.00009072942,0.00007507404,0.0002220211,0.0003003133],"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":[0.00003002607,7.520496e-7,0.000008748039,0.0000188467,0.00005759832,0.000001409457,0.000275752,0.9985658,0.0006625395,0.0002780992,0.00003074433,0.00006969657],"study_design_scores_gemma":[0.001198878,0.00003959626,2.448274e-7,0.00007440201,0.00003831202,0.00005921199,0.00006093499,0.9963445,0.001937925,0.0001240181,0.00001241022,0.000109577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0137533,0.0001222727,0.9854096,0.0001050123,0.0001355454,0.0002454639,0.0000243334,0.00004033777,0.0001641738],"genre_scores_gemma":[0.979296,3.428451e-7,0.02044488,0.0000154801,0.0001721327,0.00002506611,0.000004032865,0.00003967931,0.000002415853],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9655427,"threshold_uncertainty_score":0.3968862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006079621597138568,"score_gpt":0.182781892747811,"score_spread":0.1767022711506724,"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."}}