{"id":"W1968776767","doi":"10.1016/s0019-0578(07)60177-3","title":"A simplified predictive control algorithm for disturbance rejection","year":2005,"lang":"en","type":"article","venue":"ISA Transactions","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Control theory (sociology); Disturbance (geology); Model predictive control; Offset (computer science); Constant (computer programming); Computer science; Algorithm; Control (management); 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":[0.0003689574,0.0006350154,0.0008773337,0.000485655,0.0004519584,0.00082287,0.001262052,0.0006933487,0.006116154],"category_scores_gemma":[0.001288932,0.0003163594,0.0003339524,0.00053482,0.0003285169,0.0007716612,0.000732259,0.00094742,0.001577992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003847934,"about_ca_system_score_gemma":0.0006413431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0044913,"about_ca_topic_score_gemma":0.004939265,"domain_scores_codex":[0.9996717,0.00004290817,0.00001351276,0.00005160395,0.000188402,0.00003186816],"domain_scores_gemma":[0.9997328,0.00007513043,0.00001665805,0.00006549987,0.00009796287,0.00001187883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000383705,0.0001285231,0.0002678345,0.0001724495,0.00004992294,0.0001203117,0.00007778789,0.3407708,0.02111221,0.01938426,0.006083852,0.6114483],"study_design_scores_gemma":[0.00002956234,0.00003545282,0.000112421,0.000004750777,0.00001187201,0.00002460523,0.000002958646,0.9938023,0.002132838,0.00162807,0.002208174,0.000006967871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003286224,0.0001432686,0.9936911,0.00004348929,0.00008340103,0.00004143189,0.00002837869,0.0006961353,0.001986508],"genre_scores_gemma":[0.3829796,0.0003941943,0.6048563,0.0001986723,0.0001782156,0.0002788847,0.0003139864,0.0002216874,0.01057828],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006116154,"threshold_uncertainty_score":0.02046055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004959243726498729,"score_gpt":0.2071470112773345,"score_spread":0.2021877675508358,"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."}}