{"id":"W4404952278","doi":"10.1109/tase.2024.3506123","title":"Fault-Tolerant Leader-Follower Controller for Uncertain Nonlinear Multi-Agent Systems","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Automation Science and Engineering","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Concordia University","funders":"","keywords":"Control theory (sociology); Nonlinear system; Fault tolerance; Multi-agent system; Computer science; Control engineering; Controller (irrigation); Control reconfiguration; Robustness (evolution); Engineering; Distributed computing; Control (management); Artificial intelligence; Embedded system","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009955515,0.0002258973,0.0002477241,0.0005182416,0.0003206902,0.001069169,0.0004658368,0.00007908015,0.000002216478],"category_scores_gemma":[0.00003671482,0.0001997962,0.0001036853,0.0009910158,0.00006392929,0.001207436,0.000003797211,0.0001537704,0.00004892136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002410239,"about_ca_system_score_gemma":0.0001573404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002854244,"about_ca_topic_score_gemma":0.000002423738,"domain_scores_codex":[0.9979364,0.00002212347,0.000405071,0.0005986745,0.0005967243,0.0004409797],"domain_scores_gemma":[0.9990548,0.0001930927,0.00004915041,0.0003094984,0.0002160023,0.0001774105],"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":[0.000007109972,0.00007101559,8.740074e-7,0.0002009117,0.00006235715,0.000009052529,0.0008661972,0.9321174,0.0362968,0.002181876,0.0001227033,0.02806371],"study_design_scores_gemma":[0.0007283306,0.00005317182,0.00003387987,0.000175194,0.00001787885,0.00002398403,0.00009216442,0.9912872,0.002347473,0.000003375072,0.005009926,0.0002274557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003517448,0.0002878699,0.9905118,0.0004561744,0.003493513,0.0007580188,0.00004932914,0.0009049837,0.00002082896],"genre_scores_gemma":[0.9861331,0.00001177022,0.01311936,0.00006216097,0.00006487258,0.0003098092,0.0000018711,0.00001881479,0.0002782372],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9826156,"threshold_uncertainty_score":0.9999678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02877613469041963,"score_gpt":0.2715984078420898,"score_spread":0.2428222731516702,"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."}}