{"id":"W2113556348","doi":"10.1109/acc.2006.1657485","title":"Offline robust model predictive control with rewinding prediction","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Model predictive control; Robustness (evolution); Control theory (sociology); Quadratic programming; Weighting; Robust control; Mathematical optimization; Sequential quadratic programming; Parametric statistics; Computer science; Exponential stability; Optimal control; MIMO; Mathematics; Control system; Engineering; Control (management); Artificial intelligence; Nonlinear system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006501382,0.0001480764,0.0001649382,0.00007945286,0.00005299184,0.00002246996,0.00005488841,0.00007217253,0.000008740533],"category_scores_gemma":[0.000006460207,0.0001265546,0.00002427215,0.000137979,0.00001535879,0.0003648534,0.000004487718,0.00009542492,0.000006280202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001389513,"about_ca_system_score_gemma":0.00001339779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001569489,"about_ca_topic_score_gemma":0.00002256383,"domain_scores_codex":[0.9992304,0.00001033155,0.0002295631,0.0001643008,0.0001562703,0.0002091288],"domain_scores_gemma":[0.9996716,0.00002284417,0.00003842021,0.0001519964,0.00007580185,0.0000392874],"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":[0.00003807612,0.000009467339,0.0008260353,0.0000116467,0.00003089003,0.000001254722,0.00001628648,0.996245,0.001558962,0.000706401,0.0004779562,0.00007796899],"study_design_scores_gemma":[0.001513072,0.00004452052,0.000482549,0.00002569245,0.00003274571,0.000006625557,0.00002065774,0.9972311,0.0002913935,0.0001663599,0.00005911767,0.0001261465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003137614,0.00007175475,0.965779,0.00002292267,0.00009039599,0.0003825888,0.00003779141,0.001058605,0.02941934],"genre_scores_gemma":[0.9777645,0.000003853767,0.02096541,0.00001500527,0.0002023971,0.00007561879,0.00003913929,0.00004778322,0.0008863125],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9746268,"threshold_uncertainty_score":0.5160747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004152473532132289,"score_gpt":0.1564181537002908,"score_spread":0.1522656801681585,"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."}}