{"id":"W2027014539","doi":"10.1109/icca.2014.6871135","title":"Convex optimization based iterative learning control for iteration-varying systems under output constraints","year":2014,"lang":"en","type":"article","venue":"","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Iterative learning control; Computer science; Convex optimization; Regular polygon; Mathematical optimization; Iterative method; Control (management); Control theory (sociology); Algorithm; Mathematics; 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":[0.001249937,0.0008793385,0.0008361808,0.0002592789,0.0003695875,0.001235165,0.001008291,0.0008994589,0.001228652],"category_scores_gemma":[0.002724043,0.0002703531,0.0004721674,0.0004901084,0.001354633,0.0008316067,0.0009834624,0.001273096,0.0002475331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008874235,"about_ca_system_score_gemma":0.001028388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003913723,"about_ca_topic_score_gemma":0.002270777,"domain_scores_codex":[0.9992191,0.0002498821,0.00003524481,0.0001655042,0.0002343977,0.00009586437],"domain_scores_gemma":[0.9988588,0.0006148662,0.000193921,0.00007298563,0.0002294357,0.00002986684],"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":[0.0000605869,0.00003583796,0.0003563115,0.000125794,0.0000407705,0.0001120365,0.0001734491,0.9306687,0.004891461,0.03021137,0.0005653973,0.03275837],"study_design_scores_gemma":[0.00000402987,0.00002871038,0.00004874802,0.000003537986,0.000003250266,0.00001196378,0.000005918545,0.9969057,0.000738588,0.001881036,0.0003640377,0.000004433064],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01103774,0.0001997958,0.9855564,0.0000858608,0.00001777518,0.00002613816,0.00001069277,0.00009062397,0.002974983],"genre_scores_gemma":[0.9152225,0.0003825271,0.07968132,0.0001043289,0.00004611754,0.0001690336,0.00006067646,0.00005937669,0.004274128],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003913723,"threshold_uncertainty_score":0.007781923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00930468342355607,"score_gpt":0.2103332337711799,"score_spread":0.2010285503476238,"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."}}