{"id":"W4414549910","doi":"10.1002/acs.4083","title":"Finite‐Time Lyapunov‐Based Model Predictive Control of Unmanned Surface Vehicles Against Denial‐of‐Service Attacks: An Independent of Prediction Horizon Approach","year":2025,"lang":"en","type":"article","venue":"International Journal of Adaptive Control and Signal Processing","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Natural Science Foundation of China","keywords":"Model predictive control; Control theory (sociology); Backstepping; Robustness (evolution); Compensation (psychology); Stability (learning theory); Robust control; Control system; Tracking error","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005326084,0.0005303227,0.0005211401,0.0002765078,0.0003080128,0.0008115384,0.0007703078,0.0004484011,0.0008102966],"category_scores_gemma":[0.001009112,0.0002217775,0.0003743102,0.0002387289,0.0007055108,0.0004474794,0.0006685825,0.0008155843,0.0001165558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004775249,"about_ca_system_score_gemma":0.0008914741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008217392,"about_ca_topic_score_gemma":0.004368268,"domain_scores_codex":[0.9996821,0.00006863306,0.00001346843,0.00005841512,0.0001337286,0.00004373889],"domain_scores_gemma":[0.9995379,0.0001707214,0.0000920345,0.00004055336,0.0001377116,0.00002109182],"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":[0.00006527868,0.00002284687,0.0001805433,0.00004949194,0.00001803168,0.0000598284,0.00006456364,0.9740857,0.004407551,0.004625847,0.0003051989,0.0161151],"study_design_scores_gemma":[0.000002555582,0.0000193536,0.00003642102,0.000001849596,0.000001868177,0.000002048373,0.000002205055,0.9991853,0.0003617154,0.0002810538,0.0001042259,0.00000152043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04659756,0.0003862224,0.9480084,0.0002179827,0.0001083998,0.00002903699,0.00002328917,0.0003817356,0.004247422],"genre_scores_gemma":[0.9920012,0.0001095547,0.006831631,0.00002729228,0.00001730832,0.00003023883,0.00001889595,0.00001053342,0.0009534364],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008217392,"threshold_uncertainty_score":0.01633912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01000011195775783,"score_gpt":0.2274884303899134,"score_spread":0.2174883184321555,"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."}}