{"id":"W3195795286","doi":"10.1109/tmech.2021.3096601","title":"Global Iterative Sliding Mode Control of an Industrial Biaxial Gantry System for Contouring Motion Tasks","year":2021,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Contouring; Control theory (sociology); Iterative learning control; Nonlinear system; Computer science; Backlash; Domain (mathematical analysis); Sliding mode control; Convergence (economics); Motion control; Work (physics); Control engineering; Control (management); Engineering; Artificial intelligence; Mathematics; Physics; Robot; Mechanical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001830937,0.0002077811,0.0004142247,0.00009010443,0.0001216681,0.00006238971,0.0001669003,0.0001927988,0.000007949116],"category_scores_gemma":[0.00008142036,0.0002520139,0.0001414836,0.0003515586,0.00002750877,0.000425546,0.00002473561,0.0001540415,0.000004452236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004331462,"about_ca_system_score_gemma":0.00005694288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005841831,"about_ca_topic_score_gemma":0.00005860601,"domain_scores_codex":[0.9987636,0.0002252625,0.0002715633,0.0003604064,0.00007600411,0.0003031473],"domain_scores_gemma":[0.9991305,0.0001301828,0.0001269241,0.0002525086,0.000250077,0.00010984],"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":[0.0002465543,0.00003641996,0.006717168,0.0001524263,0.0002609436,0.0001429442,0.0002968274,0.944947,0.01309687,0.03363756,0.00002970106,0.000435586],"study_design_scores_gemma":[0.005110915,0.00009456874,0.0003829828,0.0001750235,0.0001115961,0.00001510654,0.0008673286,0.9873943,0.005356033,0.000116556,0.0001220255,0.0002535678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5742231,0.00003446601,0.4238968,0.00000446496,0.0005337169,0.0002810449,0.0001344023,0.0001629183,0.0007290409],"genre_scores_gemma":[0.999321,0.000001279015,0.0001039896,0.000006429281,0.0004043987,0.000002659632,0.00003516785,0.00002533674,0.00009976023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4250979,"threshold_uncertainty_score":0.9999932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0413118003908707,"score_gpt":0.1840830515038367,"score_spread":0.142771251112966,"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."}}