{"id":"W1982766596","doi":"10.2316/journal.201.2010.3.201-2158","title":"DESIGN OF FUZZY FLATNESS-BASED CONTROLLER FOR A DC DRIVE","year":2010,"lang":"en","type":"article","venue":"Control and Intelligent Systems","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Control theory (sociology); Flatness (cosmology); Robustness (evolution); Fuzzy logic; PID controller; Control engineering; Trajectory; Fuzzy control system; Computer science; Control system; Engineering; Control (management); Temperature control; Artificial intelligence","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":[0.001208792,0.0002776896,0.0007813604,0.0001448732,0.0001401652,0.0001793886,0.0006851801,0.0001971671,0.000002468839],"category_scores_gemma":[0.0001628072,0.0002068472,0.0001838688,0.0001465631,0.0001175112,0.0001908802,0.00003958872,0.0001644949,0.00001738272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001933245,"about_ca_system_score_gemma":0.0001114195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008791881,"about_ca_topic_score_gemma":0.000005594869,"domain_scores_codex":[0.9978586,0.0001928312,0.0007334729,0.000502345,0.000292803,0.0004199406],"domain_scores_gemma":[0.9975303,0.0009715881,0.0003732115,0.0005236503,0.0004162166,0.0001850418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001002345,0.000330432,0.001355689,0.0005000499,0.0004991678,0.00001249885,0.0007563921,0.01166338,0.1892768,0.7630932,0.001952837,0.02955729],"study_design_scores_gemma":[0.005385648,0.0006943468,0.0001785775,0.00009358508,0.00006189042,0.00002162255,0.00009372936,0.9781079,0.001749202,0.006507154,0.006712954,0.0003933929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00144953,0.001839406,0.9907493,0.0003587718,0.001871735,0.002357213,0.00001702964,0.0001070403,0.001249976],"genre_scores_gemma":[0.9961841,0.00001172978,0.002357164,0.0002220098,0.0002858502,0.0005877961,0.000001998227,0.00001683491,0.000332542],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9947345,"threshold_uncertainty_score":0.8434985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01970188313411375,"score_gpt":0.2363580716502935,"score_spread":0.2166561885161797,"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."}}