{"id":"W4280571951","doi":"10.18280/jesa.550205","title":"Adhesion Control for Freight Train Based on Improved Sliding Mode Extremum Seeking Algorithm and Barrier Lyapunov Function","year":2022,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Lubricants and Their Additives","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; National Science Foundation","keywords":"Lyapunov function; Sliding mode control; Control theory (sociology); Particle swarm optimization; Mode (computer interface); Nonlinear system; Traction (geology); Computer science; Adhesion; Controller (irrigation); Creep; Component (thermodynamics); Engineering; Algorithm; Control (management); Materials science; Artificial intelligence; Physics; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005972286,0.0002777304,0.0003556916,0.0002698611,0.0008525387,0.0002058765,0.0001525061,0.00005441336,0.0002307379],"category_scores_gemma":[0.00007870332,0.0002445243,0.000160318,0.0001733706,0.00003013381,0.00028192,0.00003219041,0.0003834307,0.000002656415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003065249,"about_ca_system_score_gemma":0.00004862482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006781931,"about_ca_topic_score_gemma":0.000001608903,"domain_scores_codex":[0.9983612,0.0002115282,0.0004392061,0.0002438353,0.0003216787,0.0004225038],"domain_scores_gemma":[0.999103,0.0003223883,0.0001715548,0.0001558622,0.0000661063,0.0001811177],"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":[0.0001987968,0.00008771941,0.0001586891,0.0002194737,0.0003043425,0.00008179433,0.0008143976,0.0434456,0.09383243,0.0003978409,0.001844584,0.8586143],"study_design_scores_gemma":[0.001918528,0.0004925525,0.006731034,0.0001283307,0.00007832092,0.0001841957,0.0002328884,0.9852612,0.0003394627,0.001234658,0.003104471,0.0002943379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03044005,0.0008268502,0.9651915,0.00007218462,0.00111901,0.0005580373,0.0004541332,0.0004323269,0.000905854],"genre_scores_gemma":[0.9919279,0.00002915296,0.007127375,0.0001613881,0.000361931,0.00008749773,0.00001531569,0.0001067535,0.0001826814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9614878,"threshold_uncertainty_score":0.9971413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097742189609584,"score_gpt":0.2149057359223498,"score_spread":0.2039283140262539,"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."}}