{"id":"W2982621088","doi":"10.1109/icstcc.2019.8885837","title":"Algebraic Nonlinear Identification and Output Tracking Control of Synchronous Generator using Differential Flatness","year":2019,"lang":"en","type":"article","venue":"","topic":"Control Systems and Identification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Control theory (sociology); Nonlinear system; Computer science; Initialization; Robustness (evolution); Nonlinear system identification; System identification; Nonlinear control; Control engineering; Artificial intelligence; Engineering; Data modeling","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":[0.00012207,0.0001133557,0.0002346427,0.0000899138,0.00003368023,0.00008020928,0.00007038242,0.00007008835,0.00004861773],"category_scores_gemma":[0.000009461795,0.000109913,0.00004856427,0.00007216516,0.00001494009,0.000195078,0.00001021512,0.00005438238,0.00002092197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003596633,"about_ca_system_score_gemma":0.00001102809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006262043,"about_ca_topic_score_gemma":0.00001739772,"domain_scores_codex":[0.9991643,0.00002262865,0.0003836349,0.0001694974,0.0001265551,0.0001333452],"domain_scores_gemma":[0.9995617,0.00002459824,0.00008144781,0.0002149808,0.0000779679,0.00003936394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007184065,0.00001628832,0.003296678,0.0001654434,0.00006056151,2.584513e-7,0.0001074694,0.004632034,0.9830663,0.0002951135,0.00001281014,0.008339892],"study_design_scores_gemma":[0.0008643317,0.00001135602,0.02450124,0.00003287458,0.00004932069,0.000004522409,0.00005129356,0.9420958,0.03209817,0.00001529725,0.0001272223,0.0001486186],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8327065,0.0003528108,0.1658896,0.000007911292,0.0005965768,0.0002950788,0.00001093421,0.00007165313,0.0000689586],"genre_scores_gemma":[0.9994563,0.00001028888,0.0001528001,0.000003821077,0.0001561088,0.000007215542,0.00001161123,0.00002451605,0.0001773262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9509681,"threshold_uncertainty_score":0.4482121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008111499737416207,"score_gpt":0.2022450675226329,"score_spread":0.1941335677852166,"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."}}