{"id":"W4386050717","doi":"10.3390/vehicles5030055","title":"Adaptive Robust Terminal Sliding Mode Control with Integral Backstepping Synthesized Method for Autonomous Ground Vehicle Control","year":2023,"lang":"en","type":"article","venue":"Vehicles","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Control theory (sociology); Backstepping; Robustness (evolution); Terminal sliding mode; Parametric statistics; Lyapunov stability; Lyapunov function; Computer science; Sliding mode control; Robust control; Adaptive control; Nonlinear system; Control engineering; Engineering; Control system; Mathematics; Control (management); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003725017,0.0005554884,0.0004364492,0.0003183478,0.0002367833,0.0005141138,0.0006685616,0.0004466033,0.00123905],"category_scores_gemma":[0.0005236486,0.0001562038,0.0004803071,0.0002720483,0.0004403873,0.0003146461,0.0004975283,0.000624979,0.0001602294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002937428,"about_ca_system_score_gemma":0.000567868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004059837,"about_ca_topic_score_gemma":0.002358487,"domain_scores_codex":[0.9998122,0.00003819614,0.00001190514,0.00003430338,0.00008547703,0.00001792576],"domain_scores_gemma":[0.9998229,0.00006489889,0.00002888141,0.00001220886,0.00006184787,0.000009256893],"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":[0.0001536445,0.00006469819,0.0005199744,0.0002174454,0.00005995314,0.000156743,0.0001833564,0.864713,0.02426973,0.01311437,0.001006045,0.09554112],"study_design_scores_gemma":[0.000006547827,0.00008571337,0.00006878428,0.000004602019,0.000004855673,0.000008882585,0.000005717149,0.9979377,0.0009108618,0.0004585658,0.0005040937,0.000003559771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0135664,0.0002309508,0.9833623,0.00004042674,0.00005396721,0.00003093017,0.0000127264,0.0002476415,0.002454711],"genre_scores_gemma":[0.9300362,0.0003195891,0.06646338,0.00004734597,0.00003462719,0.0001486521,0.00006452618,0.00002277752,0.002862893],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004059837,"threshold_uncertainty_score":0.008072436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01521694788775248,"score_gpt":0.232976594598852,"score_spread":0.2177596467110995,"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."}}