{"id":"W4362681493","doi":"10.1109/tsipn.2023.3264992","title":"Fault Estimation and Fault-Tolerant Tracking Control for Multi-Agent Systems With Lipschitz Nonlinearities Using Double Periodic Event-Triggered Mechanism","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Signal and Information Processing over Networks","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Natural Science Foundation of China","keywords":"Control theory (sociology); Lipschitz continuity; Observer (physics); Weighting; Computer science; Controller (irrigation); Nonlinear system; Linear matrix inequality; Fault tolerance; Mathematics; Control (management); Mathematical optimization; Distributed computing; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004717224,0.0002945899,0.0003565506,0.0002991038,0.0009229835,0.001525458,0.0001859288,0.0001617295,0.000002040433],"category_scores_gemma":[0.00000387361,0.0002519655,0.00007057806,0.0004863856,0.0000559305,0.00436662,0.000004431985,0.0002266412,0.000004114551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000846597,"about_ca_system_score_gemma":0.0001181642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006160775,"about_ca_topic_score_gemma":0.000007323958,"domain_scores_codex":[0.9981837,0.00005351323,0.0006537105,0.0003060659,0.0003977364,0.0004052212],"domain_scores_gemma":[0.9989358,0.00009753396,0.0003669899,0.0001693547,0.0002906426,0.000139638],"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":[0.0001929626,0.0000421601,0.000008141631,0.0002746059,0.00006277749,0.000001667656,0.001118419,0.9500538,0.0001372934,0.0003857763,0.00001179902,0.04771065],"study_design_scores_gemma":[0.004992874,0.0001480519,0.0000613607,0.0004793652,0.0000722624,0.00003393953,0.0004217013,0.9930649,0.0002738443,0.00002497973,0.0001172127,0.0003095479],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01623889,0.0001767636,0.981505,0.00007460669,0.0004626017,0.001123679,0.00007203288,0.0003381735,0.000008227413],"genre_scores_gemma":[0.9939081,0.00002635964,0.005506319,0.0001570903,0.00005907278,0.0002426745,0.00003788548,0.00001831845,0.00004415913],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9776692,"threshold_uncertainty_score":0.9999933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0283521306262894,"score_gpt":0.2637271677961819,"score_spread":0.2353750371698926,"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."}}