{"id":"W4412609969","doi":"10.1109/tcst.2025.3587910","title":"LMI-Based Robust Model Predictive Control Architecture for a Quarter Car With Series Active Variable Geometry Suspension","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Control Systems Technology","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Suspension (topology); Series (stratigraphy); Variable (mathematics); Quarter (Canadian coin); Control theory (sociology); Model predictive control; Architecture; Computer science; Geometry; Mathematics; Control (management); Artificial intelligence; Geology; Mathematical analysis; Geography; Pure mathematics; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004971492,0.0008268837,0.0007057503,0.0002823047,0.0004165503,0.0009240589,0.001229271,0.0006440851,0.002277542],"category_scores_gemma":[0.0004579797,0.0003287792,0.0004831868,0.0002511854,0.0005744592,0.0004752462,0.0007590913,0.0009700134,0.0004845635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005682611,"about_ca_system_score_gemma":0.0008397871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004681854,"about_ca_topic_score_gemma":0.003753332,"domain_scores_codex":[0.9997161,0.00004783788,0.00001721384,0.00008514974,0.00009229307,0.00004151759],"domain_scores_gemma":[0.9997814,0.00005062955,0.00005640178,0.00002712939,0.00007340523,0.00001107611],"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":[0.0001264115,0.00004320157,0.0002451334,0.0001395204,0.00004436632,0.000131122,0.0001179354,0.9226987,0.01556937,0.008654256,0.001223266,0.05100667],"study_design_scores_gemma":[0.000007344068,0.00005510763,0.0000472332,0.000002873423,0.000006345248,0.0000106456,0.000005414919,0.9974794,0.001294198,0.0004950986,0.0005925685,0.000003814888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01828681,0.0002068199,0.9739211,0.0001742698,0.00008322779,0.00004320759,0.00005595574,0.0009908535,0.006237785],"genre_scores_gemma":[0.9580211,0.0001709594,0.03808574,0.00007349752,0.00004811346,0.000123644,0.0001087729,0.00004269605,0.003325496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004681854,"threshold_uncertainty_score":0.009309232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003168616155095938,"score_gpt":0.1741394950192266,"score_spread":0.1709708788641307,"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."}}