{"id":"W1506372962","doi":"","title":"Iterative learning strategy for a class of nonlinear controllers applied to constrained batch processes","year":2004,"lang":"en","type":"article","venue":"Asian Control Conference","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Iterative learning control; Computer science; Trajectory; Convergence (economics); Process (computing); Mathematical optimization; Nonlinear system; Control theory (sociology); Exploit; Batch processing; Class (philosophy); Scheme (mathematics); Iterative method; Control (management); Iterative and incremental development; Algorithm; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00115296,0.0008458316,0.0007081034,0.0003593036,0.0003427375,0.0006267222,0.001047878,0.0008976322,0.001236036],"category_scores_gemma":[0.002505504,0.0002291918,0.0004758441,0.0003384689,0.0008672167,0.0006617873,0.0007338736,0.0009234524,0.0002647669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006038734,"about_ca_system_score_gemma":0.0008801935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003939804,"about_ca_topic_score_gemma":0.002167896,"domain_scores_codex":[0.9995198,0.0001230374,0.00003286768,0.0001116528,0.0001666436,0.000045934],"domain_scores_gemma":[0.9992586,0.0003473219,0.0001056299,0.00006073943,0.0002022978,0.00002537077],"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":[0.0001287193,0.00008580111,0.0004286984,0.0001817475,0.00006879155,0.0001447628,0.0002712106,0.8413156,0.01584997,0.03289727,0.0008394761,0.1077878],"study_design_scores_gemma":[0.000007796767,0.00007859728,0.00006935121,0.000004553429,0.000004796116,0.00001163392,0.000004399837,0.9957286,0.001696678,0.001955604,0.000432369,0.000005688043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01369141,0.0001700861,0.9839646,0.0000560414,0.00002139004,0.0000526856,0.000008895036,0.000113844,0.001920978],"genre_scores_gemma":[0.7852602,0.0003624574,0.2079819,0.0001069989,0.0000504776,0.000378754,0.00007055909,0.00005117149,0.005737535],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003939804,"threshold_uncertainty_score":0.007833779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0133507955566241,"score_gpt":0.2379943564788989,"score_spread":0.2246435609222748,"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."}}