{"id":"W3085629799","doi":"10.1109/jsyst.2020.3019169","title":"Guaranteed Performance Design for Formation Tracking and Collision Avoidance of Multiple USVs With Disturbances and Unmodeled Dynamics","year":2020,"lang":"en","type":"article","venue":"IEEE Systems Journal","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Sultan Qaboos University","keywords":"Control theory (sociology); Trajectory; Parametric statistics; Computer science; Artificial neural network; Controller (irrigation); Collision avoidance; Lyapunov function; Underactuation; Vehicle dynamics; Engineering; Collision; Control engineering; Artificial intelligence; Control (management); Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0006845591,0.000177529,0.0004022743,0.00007017729,0.0002639052,0.000348082,0.0003350916,0.0000611438,8.080864e-8],"category_scores_gemma":[0.00006812121,0.0001345529,0.00003552927,0.0002020959,0.00004510906,0.001264022,0.00002402531,0.0001412275,4.867726e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007399895,"about_ca_system_score_gemma":0.00005399618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001289477,"about_ca_topic_score_gemma":0.000008342292,"domain_scores_codex":[0.9984439,0.0001400832,0.000578323,0.000247281,0.000342547,0.0002478873],"domain_scores_gemma":[0.9985429,0.0002163911,0.0006571841,0.0001518259,0.0002946849,0.0001369836],"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":[0.001559061,0.0001222843,0.02531217,0.003182598,0.0002839458,0.00004542135,0.009120725,0.9104485,0.02883032,0.001743345,0.0004625454,0.01888907],"study_design_scores_gemma":[0.002339434,0.0004900423,0.0008669402,0.0004554638,0.00001997937,0.0003848121,0.000214692,0.9934172,0.001543388,0.00001434215,0.00009112812,0.0001625969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3214181,0.0006555265,0.6769643,0.0001105635,0.0002325054,0.0005628109,0.00002298037,0.00002677047,0.000006468182],"genre_scores_gemma":[0.9918969,0.0000559135,0.00786186,0.00002237408,0.0001093925,0.00003214866,0.000002400404,0.00001213279,0.00000687895],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6704788,"threshold_uncertainty_score":0.5486906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03663386510515897,"score_gpt":0.2206868712138958,"score_spread":0.1840530061087368,"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."}}