{"id":"W3212233749","doi":"10.1109/iecon48115.2021.9589671","title":"Robust Predictor Feedback Input Delay Compensation with Application to Daylight Harvesting Control","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Robustness (evolution); Computer science; Smith predictor; Stability (learning theory); Robust control; Compensation (psychology); Controller (irrigation); Control system; PID controller; Control engineering; Control (management); Engineering; Temperature control","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":[0.00008469994,0.0001549579,0.0001954912,0.0000568646,0.00006309206,0.00006732472,0.00008124565,0.00006268625,0.00002973415],"category_scores_gemma":[0.00004675709,0.0001458267,0.00002110728,0.0003261115,0.000009128091,0.0002927978,0.00001296576,0.00008407199,0.00006935881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001301341,"about_ca_system_score_gemma":0.00002420582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001800711,"about_ca_topic_score_gemma":0.0002079463,"domain_scores_codex":[0.9990643,0.00002850325,0.0002742497,0.0002484797,0.0001778901,0.0002066324],"domain_scores_gemma":[0.9992774,0.00006499017,0.00004898867,0.0002792315,0.0002222916,0.0001071099],"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":[0.00001310692,0.000008679478,0.0009264725,0.00002590781,0.00003322668,0.000003095524,0.00006346569,0.9823537,0.01350825,0.000919224,0.0001509595,0.001993874],"study_design_scores_gemma":[0.00114218,0.00002797615,0.002126882,0.00004711611,0.00002616787,0.00002249937,0.00004795553,0.9910007,0.002614886,0.00002294029,0.002703987,0.0002167204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007546966,0.00006826105,0.9841158,0.0002009877,0.0001077546,0.0005854749,0.000009748132,0.0005989996,0.006766035],"genre_scores_gemma":[0.9378695,0.000002445367,0.06101033,0.0001593154,0.0001423731,0.0001724831,0.00006789683,0.00004770175,0.000527925],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9303226,"threshold_uncertainty_score":0.5946642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007009004234971995,"score_gpt":0.1839927340150203,"score_spread":0.1769837297800483,"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."}}