{"id":"W4398198586","doi":"10.1109/control60310.2024.10532118","title":"Optimisation-Based Iterative Learning Control for Distributed Consensus Tracking","year":2024,"lang":"en","type":"article","venue":"","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Iterative learning control; Computer science; Convergence (economics); Tracking error; Tracking (education); Iterative method; Norm (philosophy); Control theory (sociology); Mathematical optimization; Algorithm; Control (management); Artificial intelligence; Mathematics","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":[0.0008818952,0.0005705574,0.0006489785,0.0003342821,0.0002933521,0.0005616728,0.000847313,0.0007121456,0.001156286],"category_scores_gemma":[0.002321952,0.000209964,0.0003537622,0.0005424207,0.0008610595,0.0005919492,0.001076103,0.001037465,0.0003506466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005983228,"about_ca_system_score_gemma":0.0007318203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00173167,"about_ca_topic_score_gemma":0.00119573,"domain_scores_codex":[0.9994732,0.0001530119,0.00002314896,0.0001038792,0.0002097989,0.00003700262],"domain_scores_gemma":[0.999321,0.0003969104,0.00009497096,0.00004580244,0.0001239346,0.00001749331],"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":[0.00004844924,0.00002810326,0.000182455,0.00009220833,0.00002435519,0.00003328318,0.00007421459,0.9103653,0.004215451,0.02060444,0.0006117332,0.06371998],"study_design_scores_gemma":[0.000005592624,0.00002515468,0.00003478301,0.000003573461,0.000002123762,0.000008592773,0.000002120612,0.9946537,0.0005348964,0.004215389,0.0005103998,0.000003707242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003056457,0.0001192716,0.9948559,0.00005223636,0.00001756736,0.00001314454,0.000004147355,0.00008698172,0.001794287],"genre_scores_gemma":[0.8195217,0.0003844526,0.174125,0.0001059709,0.00007911451,0.000204271,0.00006052532,0.0000871784,0.005431721],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00173167,"threshold_uncertainty_score":0.004663944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01116282551791076,"score_gpt":0.2406785945948715,"score_spread":0.2295157690769607,"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."}}