{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003115646,0.0003927061,0.0003228447,0.0001999769,0.000212677,0.0004610821,0.0004302606,0.0002791353,0.0009142077],"category_scores_gemma":[0.0006513033,0.0001358271,0.0002374951,0.0002129738,0.0004382854,0.0004403222,0.0005343828,0.0003538381,0.0002423428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002576937,"about_ca_system_score_gemma":0.0003491136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001001514,"about_ca_topic_score_gemma":0.0009679723,"domain_scores_codex":[0.9998311,0.00003709121,0.000009179501,0.00003647447,0.00007042979,0.00001574962],"domain_scores_gemma":[0.9997671,0.00006646527,0.00005040663,0.00003953858,0.00006561373,0.00001082322],"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":[0.0002167899,0.0000770331,0.0009700343,0.0002158329,0.00004029175,0.0002844362,0.0003734843,0.695229,0.1043257,0.05696556,0.0009114245,0.1403904],"study_design_scores_gemma":[0.000004988201,0.0001183638,0.0002279824,0.000004165036,0.000004313171,0.00002955531,0.000008524041,0.9904282,0.006064455,0.002396918,0.0007052651,0.000007251729],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02236119,0.00005248864,0.9752284,0.00003408511,0.00001530668,0.00002107842,0.00001317891,0.0001669846,0.002107342],"genre_scores_gemma":[0.953812,0.00009698768,0.04311605,0.00001835475,0.00001181765,0.0000483025,0.00003628356,0.000022738,0.002837439],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001001514,"threshold_uncertainty_score":0.003058374,"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."}}