{"id":"W3212048475","doi":"10.1115/1.4053026","title":"Robust Nonlinear Model Predictive Control With Model Predictive Sliding Mode for Continuous-Time Systems","year":2021,"lang":"en","type":"article","venue":"Journal of Dynamic Systems Measurement and Control","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Guelph","funders":"","keywords":"Control theory (sociology); Model predictive control; Robustness (evolution); Nonlinear system; Benchmark (surveying); Sliding mode control; Context (archaeology); Controller (irrigation); Mean squared error; Computer science; Mathematics; Control (management); Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001352947,0.000515409,0.001519275,0.0002274278,0.0001712295,0.0002150408,0.0002191105,0.0002335743,7.522394e-7],"category_scores_gemma":[0.0001806363,0.0004357455,0.0002240866,0.0001504264,0.00003749636,0.0006691915,0.00001356312,0.0003443326,0.000001012375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008324047,"about_ca_system_score_gemma":0.0003456822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000715152,"about_ca_topic_score_gemma":0.00001084063,"domain_scores_codex":[0.9963111,0.0001913743,0.0014274,0.0003928849,0.00111416,0.0005630513],"domain_scores_gemma":[0.9954044,0.0001859441,0.0008503135,0.0003133938,0.002971815,0.0002741248],"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":[0.001013285,0.00006330484,0.0001178011,0.0003675687,0.001704865,0.0000186267,0.0002459561,0.9705872,0.02556986,0.0001292029,0.00006902667,0.0001132978],"study_design_scores_gemma":[0.01375176,0.0004500257,0.00001372571,0.001261122,0.0009441788,0.0002207676,0.0006900742,0.9821337,0.00004775286,0.00004440222,0.00003331287,0.00040914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004738235,0.008934665,0.9826614,0.00006705752,0.0006920533,0.002143463,0.0003871131,0.0001462204,0.0002298169],"genre_scores_gemma":[0.9945023,0.0001037623,0.00432938,0.00002293695,0.0004045487,0.0003076388,0.00001378844,0.0001323716,0.0001832785],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.989764,"threshold_uncertainty_score":0.9998094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01183153429114764,"score_gpt":0.1960862799591753,"score_spread":0.1842547456680277,"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."}}