{"id":"W4388562214","doi":"10.1109/icstcc59206.2023.10308491","title":"Stochastic Model Predictive Control with Dynamic Chance Constraints","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"CODE","keywords":"Mathematical optimization; Model predictive control; Probabilistic logic; Constraint (computer-aided design); Computer science; Stochastic optimization; Constraint satisfaction; Controller (irrigation); Stochastic control; Optimal control; Control (management); Control theory (sociology); Mathematics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0008055906,0.0008201923,0.0008781859,0.0003946548,0.0004395919,0.001006731,0.001167672,0.0007369575,0.001810147],"category_scores_gemma":[0.002225493,0.0003998112,0.0006368181,0.0005917345,0.0009450773,0.0009947389,0.001300594,0.001422616,0.0002169282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009125489,"about_ca_system_score_gemma":0.001401801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006646601,"about_ca_topic_score_gemma":0.0044871,"domain_scores_codex":[0.9993165,0.000162451,0.0000292698,0.0001100836,0.0002994455,0.0000822088],"domain_scores_gemma":[0.9993224,0.000365653,0.0001045006,0.00006180777,0.0001163915,0.000029276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001594055,0.00000735223,0.00008009969,0.00002838152,0.000008270435,0.00003201897,0.00001913173,0.9541177,0.0008122995,0.03637739,0.0002096327,0.008291904],"study_design_scores_gemma":[0.00000317807,0.000008152961,0.00001919321,0.0000032186,0.000001944951,0.000003984102,0.000001279868,0.9941733,0.000192356,0.005285772,0.0003046368,0.000002970355],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004490278,0.00009910652,0.9930854,0.00007662552,0.00002381234,0.00001895409,0.00002032213,0.0001219369,0.002063499],"genre_scores_gemma":[0.9041023,0.0003802316,0.09084608,0.0001123023,0.00007582493,0.000188999,0.0001071516,0.00006519099,0.004121955],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006646601,"threshold_uncertainty_score":0.01321584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003903465531000087,"score_gpt":0.1925458618251708,"score_spread":0.1886423962941707,"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."}}