{"id":"W4221078200","doi":"10.1007/978-981-16-9613-8_36","title":"Robust Control Design of Active Suspension System for Quarter Car with Neural Network and Ziegler–Nichols Tuning Method","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in mechanical engineering","topic":"Vibration Control and Rheological Fluids","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Active suspension; Artificial neural network; Quarter (Canadian coin); Control theory (sociology); Suspension (topology); Computer science; Control engineering; Control (management); Engineering; Mathematics; Artificial intelligence; History","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004202825,0.0004906459,0.000977185,0.0001167463,0.00006423447,0.00002505429,0.0001693439,0.0004844552,0.00007369864],"category_scores_gemma":[0.0001209747,0.0004039987,0.0001350663,0.00009054657,0.00001758986,0.00008194881,0.00004759119,0.0009112153,3.758921e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001482658,"about_ca_system_score_gemma":0.00001851131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004385639,"about_ca_topic_score_gemma":0.000006284305,"domain_scores_codex":[0.998383,0.00006443195,0.0005025249,0.0004173723,0.0002272247,0.0004053915],"domain_scores_gemma":[0.9976439,0.001872052,0.00008958644,0.0002321225,0.00006019887,0.0001020876],"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":[0.0002233144,0.000003369084,3.359735e-7,0.0002735363,0.0001669859,0.00002239904,0.00004111571,0.9688621,0.01557501,0.01202136,0.000006833463,0.002803646],"study_design_scores_gemma":[0.001280401,0.0003490341,0.000002329844,0.0003703259,0.0001498581,0.00003938905,0.000004922293,0.9950613,0.001269916,0.0007255452,0.0003081642,0.0004387897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00004380838,0.001073153,0.9969569,0.00004953076,0.0003676345,0.001008858,0.00004579849,0.0002448793,0.0002093883],"genre_scores_gemma":[0.8930168,0.00005773777,0.1058141,0.00007374572,0.0004614876,0.0002343972,0.0000568212,0.0002256911,0.00005927769],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8929729,"threshold_uncertainty_score":0.9998412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01590424826509504,"score_gpt":0.2017545248429165,"score_spread":0.1858502765778215,"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."}}