{"id":"W2534509317","doi":"","title":"Adaptive FACTS controller based on Kalman filter estimator","year":2009,"lang":"en","type":"article","venue":"International Conference on Electric Power and Energy Conversion Systems","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Control theory (sociology); Kalman filter; Controller (irrigation); Electric power system; Estimator; Identifier; Computer science; Adaptive control; Control engineering; Adaptive estimator; Extended Kalman filter; Engineering; Power (physics); Mathematics","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":[0.0001371906,0.0002347362,0.0002681547,0.0002686309,0.00007237984,0.0001101505,0.0001858558,0.0001175722,0.0002319738],"category_scores_gemma":[0.00002695397,0.0002061991,0.00006682829,0.0001331535,0.00001787624,0.0001274243,0.000007837669,0.0001352909,0.00004432167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001530346,"about_ca_system_score_gemma":0.00004105703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000295348,"about_ca_topic_score_gemma":0.000001071427,"domain_scores_codex":[0.9987063,0.00006985368,0.0002950236,0.0002969244,0.0003956321,0.000236313],"domain_scores_gemma":[0.9993449,0.00009028825,0.00006711137,0.0001655999,0.0001829083,0.0001492153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002523541,0.000740695,0.0009702359,0.0000866155,0.0005921215,0.0001125959,0.0005863018,0.4342356,0.007760727,0.500631,0.03847998,0.01328059],"study_design_scores_gemma":[0.001042603,0.0003344998,0.0005883402,0.00007735946,0.000006213792,0.000006620298,0.00005333208,0.9886878,0.000468154,0.00008300161,0.008416873,0.0002352245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01353056,0.0003356009,0.3751387,0.00109638,0.004113658,0.0003960035,0.00008220931,0.0007230252,0.6045839],"genre_scores_gemma":[0.9983809,0.00003542522,0.0000312386,0.0005068642,0.00002874473,0.00001726728,0.00002048662,0.00001373169,0.0009653352],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9848503,"threshold_uncertainty_score":0.8408555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01495532506723933,"score_gpt":0.2215616051941499,"score_spread":0.2066062801269106,"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."}}