{"id":"W2045880387","doi":"10.1002/rnc.1390","title":"Kalman filter‐based adaptive control for networked systems with unknown parameters and randomly missing outputs","year":2008,"lang":"en","type":"article","venue":"International Journal of Robust and Nonlinear Control","topic":"Stability and Control of Uncertain Systems","field":"Engineering","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Kalman filter; Estimator; Control theory (sociology); Autoregressive model; Computer science; Bernoulli's principle; Convergence (economics); Filter (signal processing); Process (computing); Control (management); Mathematics; Engineering; Artificial intelligence; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004549763,0.0002108922,0.000553818,0.0001448175,0.00008766184,0.00009773273,0.0001664246,0.00008502301,0.00000207108],"category_scores_gemma":[0.00007489502,0.000159272,0.0001319643,0.00004614884,0.0001074022,0.0002113916,0.000005692467,0.0001801607,3.944179e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000622387,"about_ca_system_score_gemma":0.00007178447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002079848,"about_ca_topic_score_gemma":0.00001113938,"domain_scores_codex":[0.9986699,0.00008020106,0.0005541352,0.0001489575,0.0003307291,0.0002160808],"domain_scores_gemma":[0.9981315,0.0008692718,0.0002543472,0.00008540432,0.0005104622,0.0001490074],"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":[0.01321814,0.00008946838,0.006371947,0.00008657951,0.00197888,0.0001856083,0.0003182865,0.969209,0.0005042863,0.0001331068,0.0004598192,0.007444923],"study_design_scores_gemma":[0.02776181,0.0004795894,0.0006797055,0.0002894573,0.0001479252,0.0004064096,0.00009160307,0.9658554,0.00003359185,0.0000200742,0.004031133,0.0002032529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1597774,0.005003863,0.8321704,0.0009647306,0.001159563,0.0006794832,0.0000946875,0.0000443573,0.0001055068],"genre_scores_gemma":[0.9949815,0.00006367468,0.003966526,0.0001650552,0.0007424207,0.00002302849,0.00000485407,0.00002653951,0.00002639299],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8352041,"threshold_uncertainty_score":0.6494922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02136985236307525,"score_gpt":0.2156665061776018,"score_spread":0.1942966538145265,"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."}}