{"id":"W2095782597","doi":"10.1115/1.4002384","title":"Iterative Learning Control With Switching Gain Feedback for Nonlinear Systems","year":2010,"lang":"en","type":"article","venue":"Journal of Computational and Nonlinear Dynamics","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Iterative learning control; Control theory (sociology); Tracking error; Initialization; Trajectory; Nonlinear system; Computer science; Convergence (economics); Tracking (education); Control engineering; Control (management); Engineering; Artificial intelligence","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":[0.0005298861,0.0001898128,0.0003898614,0.0001516661,0.0001404134,0.0001904945,0.00009846182,0.00008583235,0.000002173492],"category_scores_gemma":[0.00009325155,0.000147559,0.00007847376,0.00009565424,0.000035469,0.0002429256,0.00000813491,0.0006995891,0.000001955316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005018446,"about_ca_system_score_gemma":0.00006522131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002706443,"about_ca_topic_score_gemma":0.00001390938,"domain_scores_codex":[0.9988719,0.000066484,0.0004979974,0.0001143171,0.0002619868,0.0001873479],"domain_scores_gemma":[0.9983181,0.0006184954,0.000292668,0.0000523882,0.0006143486,0.0001039394],"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":[0.000159214,0.00002336662,0.002985164,0.00009293479,0.0001972018,0.00001227371,0.0003890917,0.992311,0.0008719378,0.0008651593,0.00002073787,0.002071923],"study_design_scores_gemma":[0.002339034,0.0003403176,0.0008533722,0.0001229918,0.00004121828,0.000356713,0.0001808729,0.9936385,0.0000106422,0.0001447944,0.001797192,0.0001743337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4772186,0.0001227733,0.5217981,0.0001257348,0.0004173785,0.0001845658,0.00003033791,0.00003216246,0.00007030683],"genre_scores_gemma":[0.9513429,0.000004351669,0.04756594,0.00003256882,0.0008862272,0.000005873707,0.0000376108,0.00004272487,0.00008182185],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4742322,"threshold_uncertainty_score":0.601728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003495280808034045,"score_gpt":0.21070115718501,"score_spread":0.207205876376976,"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."}}