{"id":"W7114933089","doi":"","title":"Resilient Neural-Variable-Structure Consensus Control for Nonlinear MASs with Singular Input Gain Under DoS Attacks","year":2025,"lang":"","type":"article","venue":"ArXiv.org","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Nonlinear system; Robustness (evolution); Lipschitz continuity; Robust control; Adaptive control; Platoon; Controller (irrigation)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000503474,0.0006074263,0.0003673473,0.0002549323,0.0003095681,0.0004051093,0.0007708102,0.000428729,0.0004583494],"category_scores_gemma":[0.001014465,0.0001527152,0.0003113193,0.0001556996,0.0007090677,0.000446165,0.0007904021,0.0005231124,0.00008614298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004769112,"about_ca_system_score_gemma":0.0004204068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002855829,"about_ca_topic_score_gemma":0.001951482,"domain_scores_codex":[0.9997919,0.00003267888,0.00001132076,0.00006328017,0.00006717657,0.00003359971],"domain_scores_gemma":[0.9996444,0.0001006837,0.000124398,0.00003437378,0.00007672641,0.00001941628],"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":[0.00006816079,0.00003019274,0.0004559509,0.00004995656,0.00002586564,0.0001138461,0.000100878,0.9528484,0.01243055,0.007243103,0.0002537185,0.02637936],"study_design_scores_gemma":[0.00000486362,0.00004708579,0.00008615826,0.000001874366,0.00000412099,0.000007947591,0.000004724432,0.9973722,0.0009740834,0.001369634,0.0001249637,0.000002436056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08113288,0.0001702755,0.9152257,0.0001524007,0.00004626015,0.00003107099,0.00001258234,0.0003290367,0.002899827],"genre_scores_gemma":[0.9908546,0.00004958581,0.008321283,0.00002589417,0.00001376037,0.00002187577,0.000009143228,0.000007055469,0.0006967946],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002855829,"threshold_uncertainty_score":0.005678415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01942650529529865,"score_gpt":0.262286083031089,"score_spread":0.2428595777357904,"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."}}