{"id":"W4400976108","doi":"10.1109/icca62789.2024.10591925","title":"Adaptive Distributed Lyapunov-Based Model Predictive Control for Multi-UAV Formation Tracking with Weighted Directed Graphs","year":2024,"lang":"en","type":"article","venue":"","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Model predictive control; Computer science; Lyapunov function; Tracking (education); Control theory (sociology); Adaptive control; Control (management); Artificial intelligence; Nonlinear system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003560888,0.000747662,0.0005854816,0.0003576911,0.0003454567,0.0005817694,0.001091465,0.0004526589,0.0007176081],"category_scores_gemma":[0.0009366719,0.0002756802,0.0003274425,0.0004890236,0.0004760771,0.0005424429,0.0007837468,0.000679339,0.000148697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005688157,"about_ca_system_score_gemma":0.0006433094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006196636,"about_ca_topic_score_gemma":0.005942723,"domain_scores_codex":[0.9997678,0.0000539891,0.000009516619,0.00006237256,0.00007727418,0.00002906187],"domain_scores_gemma":[0.9996256,0.0001606542,0.00007885352,0.00002840413,0.00008778777,0.00001860112],"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":[0.00002182639,0.00001278542,0.0001368631,0.00003221194,0.00001441499,0.0000468579,0.00002697127,0.9778105,0.001681712,0.003449985,0.0002569097,0.01650888],"study_design_scores_gemma":[0.000002933477,0.00001270238,0.00002688945,0.000001109506,0.000001868749,0.00000378925,0.000002185908,0.9987921,0.0001356905,0.0008800864,0.0001392316,0.000001363009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01323271,0.000195189,0.9846288,0.00007460246,0.00003710862,0.00001857835,0.00001869772,0.0001796916,0.001614675],"genre_scores_gemma":[0.9648322,0.0002324645,0.03275885,0.00005136822,0.00003035956,0.00008373737,0.00005468437,0.00002541648,0.001930876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006196636,"threshold_uncertainty_score":0.01232117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02935945588962933,"score_gpt":0.2510649803093719,"score_spread":0.2217055244197426,"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."}}