{"id":"W2571988845","doi":"10.1002/rnc.3734","title":"Robust output synchronization of linear multi‐agent systems with constant disturbances via integral control","year":2017,"lang":"en","type":"article","venue":"International Journal of Robust and Nonlinear Control","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Control theory (sociology); Synchronization (alternating current); Computer science; Constant (computer programming); Controller (irrigation); Protocol (science); Observer (physics); State (computer science); Control (management); Multi-agent system; Algorithm; Artificial intelligence; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008289634,0.0002822662,0.000703614,0.0002194724,0.0002086799,0.000564793,0.001718359,0.0001082755,0.000004692773],"category_scores_gemma":[0.0003425208,0.0002024852,0.0001778629,0.00006987716,0.0002401792,0.001054808,0.0001050086,0.0002811534,0.000004294965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001283161,"about_ca_system_score_gemma":0.0002254008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001790819,"about_ca_topic_score_gemma":0.00005317113,"domain_scores_codex":[0.9973022,0.0001561327,0.001036565,0.0003119011,0.000917395,0.0002757677],"domain_scores_gemma":[0.9947742,0.0002112129,0.002215881,0.0004519388,0.002155696,0.0001910878],"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":[0.005210112,0.002352521,0.2669294,0.0003604928,0.008465229,0.001985032,0.001354309,0.63143,0.004077464,0.01065284,0.0008718784,0.06631071],"study_design_scores_gemma":[0.01174025,0.0003604672,0.005770984,0.0004953161,0.0001151924,0.0003958464,0.00009853745,0.979708,0.00008467262,0.00001449312,0.0009879466,0.0002283248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01336456,0.001401091,0.9808983,0.001340015,0.002312496,0.0003934962,0.0001771909,0.00002622071,0.00008666442],"genre_scores_gemma":[0.986178,0.00008146063,0.01283963,0.00007612828,0.000692174,0.000009274524,0.000009956786,0.00001794345,0.00009542714],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9728134,"threshold_uncertainty_score":0.8257106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0251992552285982,"score_gpt":0.2514691156728528,"score_spread":0.2262698604442546,"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."}}