{"id":"W2061840454","doi":"10.1016/j.isatra.2007.12.002","title":"Control of nonlinear processes by using linear model predictive control algorithms","year":2008,"lang":"en","type":"article","venue":"ISA Transactions","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Model predictive control; Nonlinear system; Control theory (sociology); Process (computing); Process control; Controller (irrigation); Simple (philosophy); Algorithm; Computer science; Nonlinear control; Control (management); Control engineering; Engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0000478282,0.0001927573,0.0003388479,0.00009114434,0.0001288012,0.000005897014,0.00009771207,0.0001196396,0.00001454852],"category_scores_gemma":[0.00001992136,0.0002068989,0.00008209088,0.0002617019,0.00007417515,0.0003719126,8.921874e-7,0.0001679765,0.000003548548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008078419,"about_ca_system_score_gemma":0.00008552625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002882197,"about_ca_topic_score_gemma":0.00000748496,"domain_scores_codex":[0.9989732,0.00002145354,0.0003883404,0.0001810831,0.0001988205,0.0002371075],"domain_scores_gemma":[0.9993381,0.0000852183,0.00007299774,0.0001709329,0.0002506879,0.00008205247],"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":[0.0000390221,0.00005717021,0.00002582129,0.00006496526,0.0001348595,0.000001417006,0.0002327529,0.9857766,0.01340191,0.00000191836,0.00002086245,0.0002427071],"study_design_scores_gemma":[0.002129992,0.00004145132,0.000003933081,0.00003233564,0.0001115755,0.00002153085,0.00003648735,0.9926351,0.00465687,0.00001075689,0.000148248,0.0001717632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003763899,0.0005835299,0.9935983,0.00002531399,0.0001461755,0.0004892858,0.0009259267,0.0003245667,0.0001430316],"genre_scores_gemma":[0.9746658,0.0001105588,0.02490808,0.00002403158,0.00007974778,0.00007261183,0.00001530341,0.0000584515,0.00006540118],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9709019,"threshold_uncertainty_score":0.8437092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01242718561789777,"score_gpt":0.2221536275273222,"score_spread":0.2097264419094245,"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."}}