{"id":"W2131707589","doi":"10.1109/tec.2005.847997","title":"Synchronous Generator Model Identification for Control Application Using Volterra Series","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Energy Conversion","topic":"Control Systems and Identification","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Volterra series; Control theory (sociology); Permanent magnet synchronous generator; Generator (circuit theory); Nonlinear system; Convolution (computer science); Generalization; Computer science; Voltage; Electric power system; System identification; Series (stratigraphy); Mathematics; Power (physics); Engineering; Data modeling; Control (management); Mathematical analysis; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003257975,0.000647981,0.0005708361,0.0003844791,0.0003069826,0.0004772777,0.0004724161,0.0005317012,0.002264148],"category_scores_gemma":[0.0008111514,0.0002099609,0.0004961314,0.0004412729,0.0002057669,0.0005700086,0.0002357615,0.0006070466,0.0008888024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002528119,"about_ca_system_score_gemma":0.0003980239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001475875,"about_ca_topic_score_gemma":0.001536974,"domain_scores_codex":[0.9998351,0.00004892326,0.00001077515,0.00003215492,0.00006348032,0.000009500502],"domain_scores_gemma":[0.9998247,0.00006627617,0.00001930957,0.00003959709,0.00004517905,0.000004993295],"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":[0.00008409541,0.00006993283,0.0005204275,0.000305249,0.00005724508,0.0002326616,0.0001321864,0.6751299,0.0428049,0.03239081,0.002129631,0.246143],"study_design_scores_gemma":[0.000003476133,0.00002576827,0.0001203763,0.000007656166,0.000006540907,0.00004906705,0.000007838376,0.9892847,0.004195189,0.003356076,0.002936849,0.000006476434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004990204,0.0001807261,0.9923747,0.00004928043,0.00004251964,0.00002242397,0.00002830213,0.0005688332,0.001743078],"genre_scores_gemma":[0.7112947,0.0010944,0.2792739,0.00007281896,0.0000855555,0.0002542623,0.0002487575,0.0002010327,0.007474574],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002264148,"threshold_uncertainty_score":0.00757432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008877290546534612,"score_gpt":0.2016273642801867,"score_spread":0.1927500737336521,"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."}}