{"id":"W4391495714","doi":"10.1109/etfg55873.2023.10407820","title":"Integral Reinforcement Learning Control for a Class of Unknown Nonlinear Systems with an Application to a Microgrid System","year":2023,"lang":"en","type":"article","venue":"","topic":"Adaptive Dynamic Programming Control","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Fundamental Research Funds for the Central Universities; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Microgrid; Reinforcement learning; Nonlinear system; Class (philosophy); Computer science; Control (management); Control theory (sociology); Reinforcement; Control system; Control engineering; Artificial intelligence; Engineering; Structural engineering; Electrical engineering; Physics","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":[0.0007101754,0.0006049296,0.0005462148,0.000237984,0.0003562226,0.0006459838,0.000644095,0.0005819649,0.001301393],"category_scores_gemma":[0.0008571134,0.000155944,0.0003645009,0.0002249103,0.0007503715,0.0003999414,0.0006052381,0.0008733735,0.0001330564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004909816,"about_ca_system_score_gemma":0.0005082592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004082089,"about_ca_topic_score_gemma":0.002339026,"domain_scores_codex":[0.9997461,0.00006374194,0.00001133085,0.00006277946,0.00007918482,0.00003690431],"domain_scores_gemma":[0.9997153,0.0001448259,0.0000455002,0.00001613452,0.00006168165,0.00001649571],"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":[0.00006992029,0.00004793829,0.0004970393,0.0001610345,0.00003633442,0.0002123399,0.0001264428,0.9163405,0.005060975,0.0201938,0.000722693,0.05653096],"study_design_scores_gemma":[0.000004617089,0.00002761415,0.00005874989,0.000002418523,0.000003239927,0.00001633027,0.00000419123,0.9981093,0.0003174956,0.00109329,0.0003599694,0.00000269145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02125007,0.000398084,0.9732322,0.0001545807,0.00005421658,0.00003879017,0.00001219216,0.0001579714,0.004701873],"genre_scores_gemma":[0.9564334,0.0002915467,0.03987087,0.00005413746,0.00004575378,0.000068221,0.00001885399,0.00001943021,0.003197678],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004082089,"threshold_uncertainty_score":0.008116663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008847576481085459,"score_gpt":0.2437643297133468,"score_spread":0.2349167532322614,"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."}}