{"id":"W4206332145","doi":"10.1002/rnc.6011","title":"Event‐triggered robust model predictive control for linear discrete‐time systems with a guaranteed average inter‐execution time","year":2022,"lang":"en","type":"article","venue":"International Journal of Robust and Nonlinear Control","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"China Scholarship Council","keywords":"Model predictive control; Control theory (sociology); Bounded function; Computer science; Discrete time and continuous time; Set (abstract data type); Robust control; Mathematical optimization; Stability (learning theory); State (computer science); Invariant (physics); Linear system; Robustness (evolution); Control (management); Mathematics; Control system; Algorithm; Engineering; Artificial intelligence","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":[0.0006747587,0.0007587995,0.0006392843,0.0002456605,0.0003048553,0.0006994368,0.0009315286,0.000518709,0.001239957],"category_scores_gemma":[0.0009402152,0.0002331699,0.0005087128,0.0002804766,0.0005393822,0.0004122166,0.0005832526,0.0008147854,0.0001392826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005208071,"about_ca_system_score_gemma":0.000822589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003569785,"about_ca_topic_score_gemma":0.002016088,"domain_scores_codex":[0.9994634,0.0001147063,0.00002124322,0.000105905,0.0002194226,0.00007532755],"domain_scores_gemma":[0.9995993,0.0001562012,0.00008851752,0.00003787304,0.000099191,0.00001900943],"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":[0.0001068632,0.00003680194,0.0001269959,0.00006199773,0.00001793882,0.00008696695,0.0000352465,0.9700738,0.006352098,0.007812406,0.0003419632,0.01494698],"study_design_scores_gemma":[0.000004364087,0.00002382766,0.00003502574,0.000001330164,0.000002114563,0.000003153062,0.000001263138,0.9985406,0.0007699988,0.0005015873,0.0001149766,0.000001743745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02297696,0.0001355219,0.9732704,0.00008184665,0.00004015586,0.00003438249,0.0000291584,0.0004255909,0.003005991],"genre_scores_gemma":[0.9806957,0.00006980771,0.01784023,0.00002462567,0.00001508364,0.000063654,0.00004135745,0.00001861281,0.001231062],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003569785,"threshold_uncertainty_score":0.007098019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005877243779967308,"score_gpt":0.2080161355394956,"score_spread":0.2021388917595283,"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."}}