{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001558119,0.0012207,0.001363468,0.0006142515,0.0005587291,0.001421209,0.001091848,0.0008756813,0.001183568],"category_scores_gemma":[0.002523841,0.0007741156,0.0007820544,0.001146517,0.0009113789,0.0009479016,0.001212655,0.001264409,0.0001593881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001635376,"about_ca_system_score_gemma":0.002437276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02278521,"about_ca_topic_score_gemma":0.0136379,"domain_scores_codex":[0.9993011,0.0002319786,0.00002782463,0.0001251734,0.000244353,0.00006956805],"domain_scores_gemma":[0.9993039,0.0004131194,0.00008822459,0.00003411457,0.0001434387,0.00001712267],"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":[0.00001035883,0.000008718732,0.00004925489,0.00001706548,0.000008941277,0.0000116074,0.00001013727,0.9926979,0.0001573485,0.004072038,0.00009979811,0.002856784],"study_design_scores_gemma":[0.000001636234,0.000002832721,0.00001137571,7.729826e-7,0.000001268278,5.912076e-7,7.365174e-7,0.9992509,0.00003466853,0.0006331476,0.00006095966,9.635073e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01525601,0.0003430111,0.9794709,0.0001581569,0.0000347198,0.00003988306,0.00004161698,0.0001513265,0.004504379],"genre_scores_gemma":[0.9173534,0.0004693205,0.07729407,0.00008477789,0.00004015853,0.0003475401,0.0001579777,0.00006540228,0.004187359],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02278521,"threshold_uncertainty_score":0.04530519,"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."}}