{"id":"W2791154838","doi":"10.1109/tie.2018.2811367","title":"UDE-Based Robust Command Filtered Backstepping Control for Close Formation Flight","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Electronics","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"China Scholarship Council","keywords":"Backstepping; Robustness (evolution); Control theory (sociology); Aerodynamics; Nonlinear system; Robust control; Acceleration; Engineering; Computer science; Control engineering; Control system; Aerospace engineering; Adaptive control; Control (management); Physics; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003375724,0.0002970553,0.0003748592,0.0002124051,0.0002900431,0.00008113987,0.0002053838,0.0003692365,0.00005605615],"category_scores_gemma":[0.00002046958,0.0003113809,0.0001962714,0.0002527584,0.00006070614,0.0002802956,4.689114e-7,0.0005687682,0.00005777636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005198715,"about_ca_system_score_gemma":0.000164178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008987953,"about_ca_topic_score_gemma":0.0002276046,"domain_scores_codex":[0.9983437,0.00008546418,0.0005160945,0.0002395711,0.0002252853,0.0005898908],"domain_scores_gemma":[0.9989617,0.0003018443,0.0001025107,0.0003226051,0.0001895968,0.0001217799],"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":[0.00249522,0.0002436505,0.000004018799,0.0001001387,0.0006266344,0.000002959947,0.000232616,0.9150035,0.02301657,0.0004405358,0.009362261,0.04847191],"study_design_scores_gemma":[0.009814027,0.001091431,0.000001730621,0.00009461454,0.0001499393,0.000006686285,0.00002283726,0.8614553,0.08061998,0.00005537102,0.04629636,0.0003917643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008093507,0.0001047389,0.987482,0.0002328566,0.001791875,0.001323247,0.0002266928,0.0003774954,0.0003675544],"genre_scores_gemma":[0.9974385,0.000009349723,0.0007790702,0.0001229889,0.00114377,0.0002334277,0.00003048748,0.00008001681,0.0001624146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.989345,"threshold_uncertainty_score":0.9999338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04077398492853737,"score_gpt":0.2384527688266766,"score_spread":0.1976787838981393,"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."}}