{"id":"W2768458048","doi":"10.1016/j.rcim.2017.11.017","title":"Position domain nonlinear PD control for contour tracking of robotic manipulator","year":2017,"lang":"en","type":"article","venue":"Robotics and Computer-Integrated Manufacturing","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Position (finance); Nonlinear system; Domain (mathematical analysis); Tracking (education); Computer science; Contouring; Motion control; Controller (irrigation); Artificial intelligence; Time domain; Control engineering; Computer vision; Engineering; Control (management); Robot; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002167629,0.0002961669,0.0005544085,0.0001054119,0.0003105671,0.0003700094,0.0002542859,0.0001372301,0.000003333389],"category_scores_gemma":[0.00001716358,0.0002760724,0.0001243905,0.00001994111,0.00005206776,0.0002240815,0.00003451949,0.0002317817,0.000002763858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000690023,"about_ca_system_score_gemma":0.00001337934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004979538,"about_ca_topic_score_gemma":0.00002756834,"domain_scores_codex":[0.9987831,0.00004243238,0.0004295558,0.0002655872,0.0001349437,0.0003443728],"domain_scores_gemma":[0.9990937,0.0001239498,0.0002184507,0.0003542933,0.0001144093,0.00009526707],"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":[0.00006887585,0.00004129959,0.0008492919,0.0004095773,0.0003401403,0.0000231337,0.0002705249,0.9764443,0.007920184,0.002509703,0.00007381687,0.01104913],"study_design_scores_gemma":[0.002067664,0.000172677,0.009903583,0.0003620323,0.00006578278,0.00002556468,0.00003705981,0.9774325,0.00902971,0.0003132886,0.0002807128,0.0003093467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2128946,0.0001344188,0.78544,0.0000949726,0.0007106001,0.0004746441,0.00002072835,0.0001369724,0.00009299171],"genre_scores_gemma":[0.9735495,0.000008701157,0.02589974,0.00002927264,0.0003811191,0.00001564399,0.00002272071,0.000056928,0.00003632705],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7606549,"threshold_uncertainty_score":0.9999691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0118406320244847,"score_gpt":0.2234979072728821,"score_spread":0.2116572752483974,"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."}}