{"id":"W2012487390","doi":"10.1115/imece2005-80498","title":"Precision Tracking Controller Design for High Speed Feed Drives","year":2005,"lang":"en","type":"article","venue":"","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Band-stop filter; Ball screw; Robustness (evolution); Vibration; Tracking (education); Computer science; Filter (signal processing); Sliding mode control; Frequency domain; Feed forward; Robust control; Ball (mathematics); Control engineering; Control system; Low-pass filter; Engineering; Acoustics; Physics; Control (management); Artificial intelligence; Mathematics; Mechanical engineering; Computer vision","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":[0.0003418811,0.0001697871,0.000281745,0.00008637978,0.00007204695,0.0001088479,0.0001149289,0.00008574277,0.0001041598],"category_scores_gemma":[0.0001107268,0.0001427761,0.00007579384,0.0000695737,0.00001126619,0.000227558,0.000007277578,0.0001016869,0.0001295808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007655366,"about_ca_system_score_gemma":0.000006403439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004749758,"about_ca_topic_score_gemma":0.0000054324,"domain_scores_codex":[0.9990636,0.00006452158,0.0002853505,0.0001750404,0.0001319267,0.0002795794],"domain_scores_gemma":[0.9992331,0.0004722366,0.00003633996,0.0001269099,0.00007887022,0.00005256028],"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":[0.000137207,0.00002374945,0.0001283272,0.00002822289,0.0001332516,0.000001137335,0.0008099476,0.7383423,0.1967725,0.001906145,0.007075394,0.05464183],"study_design_scores_gemma":[0.003512931,0.00009943637,0.001484116,0.00004513189,0.0000204657,0.000003032025,0.00004259496,0.9514047,0.02502533,0.0002161097,0.01787352,0.0002726641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04631799,0.0002642282,0.9479007,0.0002361108,0.0003357861,0.001054441,0.000002989136,0.0006086827,0.003279045],"genre_scores_gemma":[0.9718071,0.000002643167,0.02362521,0.00006582322,0.0005530316,0.00004636946,0.000003692313,0.00005046893,0.003845623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9254891,"threshold_uncertainty_score":0.582224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0171623477804929,"score_gpt":0.2376920197656683,"score_spread":0.2205296719851754,"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."}}