{"id":"W2781838712","doi":"10.1109/tiv.2017.2788186","title":"${{\\mathcal L}_1}$ Adaptive Control of Vehicle Lateral Dynamics","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Vehicles","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robustness (evolution); Control theory (sociology); Adaptive control; Controller (irrigation); Computer science; Vehicle dynamics; Transient (computer programming); Control signal; Trajectory; Control engineering; Engineering; Control system; Control (management); Physics; Aerospace engineering; Artificial intelligence; Biology","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":[0.00009220221,0.0003187243,0.0001431476,0.0001845206,0.0001892782,0.0003617911,0.0006131796,0.000296238,0.0138132],"category_scores_gemma":[0.0002672603,0.000061771,0.0001746789,0.0001972458,0.0002092054,0.0002480037,0.0003918122,0.0002819556,0.001960288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002082195,"about_ca_system_score_gemma":0.0002255585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003522469,"about_ca_topic_score_gemma":0.003272569,"domain_scores_codex":[0.9999279,0.000009491076,0.000003691839,0.00002150661,0.00002877711,0.000008742305],"domain_scores_gemma":[0.9999418,0.00001570827,0.000007719882,0.000008712504,0.00002225932,0.00000365664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001620862,0.00009155594,0.0007652696,0.0002256587,0.00002998766,0.0002010272,0.00009020029,0.2321545,0.08737103,0.05594995,0.01362394,0.6093348],"study_design_scores_gemma":[0.00001662258,0.00009392854,0.0004990239,0.00001697907,0.000009125488,0.00007354993,0.00001201735,0.9543993,0.01177657,0.00401107,0.02907393,0.00001788651],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01990659,0.0002875978,0.9384345,0.0002168917,0.0001982751,0.00004417038,0.00009714717,0.002393739,0.03842105],"genre_scores_gemma":[0.7859109,0.0005836949,0.1621464,0.00027551,0.0001503324,0.0001433469,0.0002857781,0.0002880005,0.05021604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0138132,"threshold_uncertainty_score":0.04620975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01031375822488438,"score_gpt":0.2107164174203351,"score_spread":0.2004026591954507,"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."}}