{"id":"W4385488776","doi":"10.3390/drones7080503","title":"Fault Detection and Fault-Tolerant Cooperative Control of Multi-UAVs under Actuator Faults, Sensor Faults, and Wind Disturbances","year":2023,"lang":"en","type":"article","venue":"Drones","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Jiangsu Province; Government of Jiangsu Province; Nanjing University of Aeronautics and Astronautics; Chinese Aeronautical Establishment; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Control theory (sociology); Backstepping; Actuator; Fault detection and isolation; Fault (geology); Lyapunov function; Computer science; Engineering; Control engineering; Control (management); Adaptive control; Nonlinear system; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003865405,0.0006946851,0.0005439158,0.0002267211,0.0004276904,0.0005447348,0.0007761768,0.0006142532,0.0003360352],"category_scores_gemma":[0.0007804508,0.0001962573,0.0003514992,0.0002018785,0.0005226929,0.0005328882,0.0007172761,0.0005136269,0.00005739685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003051894,"about_ca_system_score_gemma":0.0004360167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004953591,"about_ca_topic_score_gemma":0.00277617,"domain_scores_codex":[0.9997216,0.00004156155,0.00001899458,0.00009160242,0.0000702081,0.0000561086],"domain_scores_gemma":[0.9995478,0.0001137105,0.0001590851,0.00004228284,0.0001025762,0.00003451525],"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":[0.0002145333,0.00006694383,0.002033214,0.0001500796,0.00007537573,0.0004747642,0.0003592746,0.9186582,0.02694345,0.005331172,0.0004879698,0.04520511],"study_design_scores_gemma":[0.00001325592,0.0001458194,0.000377622,0.000004389805,0.00001195643,0.00003159885,0.00003623475,0.9968509,0.001648529,0.0006615039,0.0002133015,0.000004820154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1896344,0.0003593336,0.8076938,0.0001480678,0.00008663999,0.00003823441,0.00002384643,0.0001913809,0.001824177],"genre_scores_gemma":[0.994444,0.00005298068,0.005003676,0.00001500421,0.000008316923,0.0000215185,0.00001156989,0.000002106747,0.0004408662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004953591,"threshold_uncertainty_score":0.009849548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01687773053502796,"score_gpt":0.2473243046915721,"score_spread":0.2304465741565441,"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."}}