{"id":"W3181177314","doi":"10.1109/icps49255.2021.9468208","title":"A convex combination strategy in event-triggered robust MPC for linear discrete-time systems with bounded disturbances","year":2021,"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":"Control theory (sociology); Bounded function; Convex combination; Robustness (evolution); Linear system; Robust control; Computer science; Discrete time and continuous time; Regular polygon; Model predictive control; Convex optimization; Controller (irrigation); Mathematics; Control system; Control (management); 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":[0.0009552467,0.001188996,0.0008342238,0.0003734864,0.0003343972,0.0008083355,0.001133112,0.0006109128,0.001271584],"category_scores_gemma":[0.001266698,0.0004575402,0.0007018286,0.0004979733,0.0006572652,0.001168991,0.0010803,0.001140563,0.0002674565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004509918,"about_ca_system_score_gemma":0.0003979981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007397442,"about_ca_topic_score_gemma":0.0005993776,"domain_scores_codex":[0.9988868,0.0003425135,0.00005294751,0.0002082917,0.0004267636,0.00008271968],"domain_scores_gemma":[0.9994814,0.0002044454,0.0001030982,0.00005910795,0.000113549,0.00003852998],"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":[0.0003079061,0.00009654586,0.0002547573,0.0001747245,0.00009864046,0.0002662906,0.0001034933,0.8592031,0.02532518,0.02103987,0.0007831082,0.09234641],"study_design_scores_gemma":[0.0000108547,0.0002091286,0.00008706492,0.000006995579,0.00001199889,0.0000469573,0.000006106415,0.9936626,0.003259202,0.001957272,0.0007312887,0.00001057679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008702473,0.0001518524,0.9891647,0.00004299265,0.00002073081,0.0000402352,0.000008512818,0.0001018887,0.001766612],"genre_scores_gemma":[0.8859727,0.0002769431,0.1107804,0.00008944434,0.00004344357,0.00015769,0.0000581778,0.00005378104,0.002567563],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001271584,"threshold_uncertainty_score":0.005051911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00872066074027249,"score_gpt":0.2169728464047948,"score_spread":0.2082521856645222,"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."}}