{"id":"W2157808725","doi":"10.1109/acc.2007.4282963","title":"Tuning to Stabilize Adaptive Internal Model Controller for Periodic Disturbance Cancellation","year":2007,"lang":"en","type":"article","venue":"Proceedings of the ... American Control Conference/Proceedings of the American Control Conference","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Control theory (sociology); Internal model; Minimum phase; Active noise control; Controller (irrigation); Computer science; Adaptive control; Stability (learning theory); Noise (video); Control (management); Transfer function; Engineering; Noise reduction; Artificial intelligence","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":[0.0003249835,0.0003966491,0.0003742704,0.0002265661,0.0003007818,0.0004270672,0.0006105577,0.0003939911,0.001302516],"category_scores_gemma":[0.0009658253,0.0001630652,0.0002976938,0.0001305509,0.0003005845,0.0002343811,0.0004701118,0.0006143703,0.0004545247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002014009,"about_ca_system_score_gemma":0.0003246212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001093439,"about_ca_topic_score_gemma":0.0008933715,"domain_scores_codex":[0.9997527,0.00003112206,0.000009906937,0.00004689469,0.0001327316,0.00002667875],"domain_scores_gemma":[0.9997285,0.00008022584,0.0000406283,0.00003923533,0.00009936488,0.000012012],"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":[0.0001607275,0.0001514534,0.001034938,0.0002410143,0.00008677123,0.0002124635,0.000401857,0.4696232,0.1589702,0.01981281,0.003755203,0.3455493],"study_design_scores_gemma":[0.00002685445,0.0001043329,0.0002947811,0.00000737806,0.00001064935,0.00007093303,0.00001026271,0.9858914,0.009941966,0.001352992,0.002277663,0.00001089171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01823386,0.00006271706,0.9773411,0.00004077696,0.00004458227,0.00002248023,0.000006037561,0.00076944,0.003479148],"genre_scores_gemma":[0.8731316,0.00007867246,0.123201,0.00008778513,0.00003152877,0.00009465522,0.00004064266,0.00008721711,0.003246703],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001302516,"threshold_uncertainty_score":0.004357338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01559619483707254,"score_gpt":0.2454921997351203,"score_spread":0.2298960048980478,"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."}}