{"id":"W4386439316","doi":"10.1109/tmech.2023.3273395","title":"Distributed Adaptive Dynamic Event-Triggered Control for Multiple Quadrotors","year":2023,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de la Défense Nationale; Government of Canada","keywords":"Control theory (sociology); Sliding mode control; Integral sliding mode; Underactuation; Lemma (botany); Computer science; Lyapunov function; Lyapunov stability; Nonlinear system; Adaptive control; Manifold (fluid mechanics); Control (management); Engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":[],"category_scores_codex":[0.0007716581,0.0005196162,0.0006310222,0.0004403086,0.0005986305,0.0002178135,0.001300875,0.0002974751,0.00001822821],"category_scores_gemma":[0.00006915203,0.0005342485,0.0006338168,0.001382014,0.00005810252,0.0005914697,0.00001131806,0.0004473168,0.0005244625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007002876,"about_ca_system_score_gemma":0.0002963315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006781574,"about_ca_topic_score_gemma":0.0001534581,"domain_scores_codex":[0.9961239,0.0002528442,0.0007803279,0.001016881,0.00067162,0.001154419],"domain_scores_gemma":[0.9969844,0.0009116664,0.000299574,0.001196634,0.0002902555,0.0003174243],"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":[0.001095737,0.001341202,0.00003609722,0.0001702777,0.001547343,0.00007033454,0.0006702234,0.9013183,0.01482846,0.01809233,0.002455778,0.05837388],"study_design_scores_gemma":[0.005806859,0.0004719135,0.00007195215,0.00005554805,0.00009607182,0.000007054338,0.0001959709,0.9863653,0.002326296,0.001348756,0.002704476,0.0005498565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003123377,0.00006918101,0.9847195,0.001107057,0.002554229,0.002935939,0.003938864,0.001539868,0.00001198111],"genre_scores_gemma":[0.9932272,0.00002734443,0.004058413,0.0001169565,0.00005480488,0.001813016,0.0002061591,0.00006903709,0.0004270241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9901038,"threshold_uncertainty_score":0.9997109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01857981827120461,"score_gpt":0.2601504642875828,"score_spread":0.2415706460163782,"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."}}