{"id":"W2003677943","doi":"10.1002/acs.1193","title":"Robust adaptive MPC for constrained uncertain nonlinear systems","year":2010,"lang":"en","type":"article","venue":"International Journal of Adaptive Control and Signal Processing","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Hatch (Canada)","funders":"","keywords":"Parameterized complexity; Minimax; Control theory (sociology); Model predictive control; Mathematical optimization; Lipschitz continuity; Computer science; Nonlinear system; Stability (learning theory); Simple (philosophy); Adaptive control; Computation; Mathematics; Control (management); Algorithm; Artificial intelligence; Machine learning","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":[0.0003656012,0.0005505499,0.0005737142,0.0002116511,0.000177131,0.0005546636,0.0005265631,0.0004783673,0.00116503],"category_scores_gemma":[0.001180156,0.0001959796,0.0003224002,0.000307216,0.0004005303,0.0004144404,0.000622159,0.0006611178,0.0001553449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003802077,"about_ca_system_score_gemma":0.0004349233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004720416,"about_ca_topic_score_gemma":0.001940085,"domain_scores_codex":[0.9997855,0.00006010322,0.000009023814,0.0000512992,0.00007383817,0.00002016868],"domain_scores_gemma":[0.999701,0.0001662008,0.00005617448,0.00002264031,0.00004607453,0.000007858712],"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":[0.00002709718,0.000009820072,0.0001096093,0.00005520144,0.0000241811,0.00005898891,0.00001981448,0.9676374,0.003958398,0.007880884,0.0003710677,0.01984766],"study_design_scores_gemma":[0.000002771731,0.000007283045,0.00004465207,0.000001633241,0.000001485718,0.000003365047,0.000001153317,0.9981796,0.0003132028,0.001209068,0.0002342968,0.000001622978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02463544,0.0004930521,0.9707403,0.0001627437,0.00003189551,0.0000222658,0.00003842075,0.000255348,0.003620453],"genre_scores_gemma":[0.9538099,0.0003347014,0.04251563,0.00006287479,0.00004931081,0.00007295266,0.00007612605,0.00003367574,0.003044839],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004720416,"threshold_uncertainty_score":0.009385884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01652370800004385,"score_gpt":0.2372060257049836,"score_spread":0.2206823177049398,"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."}}