{"id":"W3047948263","doi":"10.1109/itec48692.2020.9161552","title":"Comprehensive Online Parameters Identification of Wound Rotor Synchronous Machine (WRSM) by Proposing Two New Parameters and Using Kalman Observer","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Extended Kalman filter; Kalman filter; Observer (physics); Rotor (electric); Computer science; Identification (biology); Control theory (sociology); Estimation theory; Control engineering; Artificial intelligence; Engineering; Algorithm; Mechanical engineering","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":[0.0004208795,0.0007895171,0.0008956476,0.0004632077,0.0002418071,0.0006391153,0.0006287912,0.0007272467,0.0009426424],"category_scores_gemma":[0.001354694,0.0004290532,0.0006807457,0.0003123909,0.0003940783,0.001550678,0.0006564989,0.0008460787,0.0005548142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002146971,"about_ca_system_score_gemma":0.00044078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001078688,"about_ca_topic_score_gemma":0.0009550888,"domain_scores_codex":[0.9994935,0.00009606516,0.00004100571,0.0001285202,0.0002071824,0.00003378314],"domain_scores_gemma":[0.9994413,0.0001285498,0.0001328604,0.0001299696,0.0001477204,0.00001954199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002259533,0.0000847081,0.002285657,0.0006989231,0.000158884,0.0003183444,0.0003034257,0.4227178,0.07222295,0.01550506,0.001990385,0.483488],"study_design_scores_gemma":[0.00002022423,0.0001613803,0.001057584,0.00003262365,0.00003522244,0.0002373359,0.00002945233,0.9728662,0.01474551,0.004071899,0.006694923,0.00004767273],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003300663,0.0001711418,0.9957962,0.0000187654,0.00003136798,0.000009518509,0.00001377797,0.0002597784,0.0003988329],"genre_scores_gemma":[0.6754335,0.0008617268,0.3195255,0.00005546053,0.000104631,0.0001272472,0.0002305192,0.0001365311,0.003525011],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001078688,"threshold_uncertainty_score":0.003153443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03109388039713755,"score_gpt":0.2627042705735663,"score_spread":0.2316103901764288,"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."}}