{"id":"W2991033378","doi":"10.1115/dscc2019-8945","title":"Periodic Tracking Control Using Gain-Scheduled Fourier Series-Based Internal Models","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Control theory (sociology); Internal model; Fourier series; Controller (irrigation); Computer science; Tracking (education); Stability (learning theory); Tracking error; Series (stratigraphy); Control engineering; Control (management); Engineering; Mathematics; 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":[0.0004701497,0.0005208366,0.0003932182,0.0002657011,0.0002692696,0.0006653398,0.0006749185,0.0003678641,0.001364419],"category_scores_gemma":[0.0007307735,0.0001928881,0.0004457817,0.0001409962,0.0004906387,0.0004836446,0.0003972661,0.0005734308,0.0003194834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003690045,"about_ca_system_score_gemma":0.000508888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001655446,"about_ca_topic_score_gemma":0.001522815,"domain_scores_codex":[0.9997764,0.00004136075,0.00001055764,0.00004113919,0.0001064015,0.00002407582],"domain_scores_gemma":[0.9997135,0.0000820565,0.00005811733,0.00004957367,0.00008418446,0.00001251803],"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":[0.0001809173,0.0001340327,0.0004942716,0.0001460259,0.00005989034,0.0001184727,0.0001510765,0.8150612,0.06753437,0.02878398,0.001145238,0.0861905],"study_design_scores_gemma":[0.00000771788,0.00006426096,0.00007193743,0.000005371193,0.000006935551,0.00001670059,0.000003149039,0.9934593,0.004793087,0.00100266,0.0005628837,0.000005920778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02699529,0.00009519188,0.9667962,0.00004924921,0.00005803827,0.00002833173,0.00001752912,0.0006636113,0.00529667],"genre_scores_gemma":[0.9365772,0.00008776403,0.06053802,0.00004022789,0.00002453775,0.00006203421,0.00004203221,0.00004679303,0.00258139],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001655446,"threshold_uncertainty_score":0.004564404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01085430352370626,"score_gpt":0.2104441760413318,"score_spread":0.1995898725176256,"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."}}