{"id":"W2494792419","doi":"10.1016/j.ifacol.2016.07.089","title":"Grey Wolf Optimizer-Based Approach to the Tuning of Pi-Fuzzy Controllers with a Reduced Process Parametric Sensitivity","year":2016,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"National Authority for Scientific Research and Innovation","keywords":"Control theory (sociology); Sensitivity (control systems); Parametric statistics; Nonlinear system; Servomechanism; Mathematics; Fuzzy control system; Fuzzy logic; Servo; Position (finance); Engineering; Computer science; Control engineering; Control (management); Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001046655,0.0003232932,0.0006153321,0.0002039287,0.0001768545,0.00009703983,0.0008588952,0.0001052295,0.000002121752],"category_scores_gemma":[0.0003896646,0.0001553603,0.0001455485,0.001306476,0.0001405506,0.0002689528,0.0000937507,0.0001690439,0.00001769224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007539901,"about_ca_system_score_gemma":0.0002776124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001194521,"about_ca_topic_score_gemma":0.0000263463,"domain_scores_codex":[0.9973419,0.0003230826,0.0004031694,0.000705652,0.0006792886,0.0005469185],"domain_scores_gemma":[0.9976539,0.000665199,0.0002304328,0.0008841187,0.0003505653,0.0002157674],"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":[0.006688482,0.004279962,0.006705671,0.000700694,0.00172985,0.000359665,0.01188402,0.5429763,0.1575195,0.03024559,0.0002369629,0.2366733],"study_design_scores_gemma":[0.02082679,0.002327671,0.004768945,0.0007901829,0.0002068276,0.0002220381,0.001830452,0.9605067,0.005772943,0.0005046547,0.0003171337,0.0019256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1882239,0.0001705208,0.7934051,0.009000059,0.0002231739,0.001450633,0.00002869609,0.0002498105,0.007248111],"genre_scores_gemma":[0.8699486,0.000002602162,0.1289182,0.0006684251,0.0001196243,0.0001045135,0.000002724837,0.00001906339,0.000216231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6817247,"threshold_uncertainty_score":0.6335407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01720699442260362,"score_gpt":0.226488579917011,"score_spread":0.2092815854944073,"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."}}