{"id":"W2792955766","doi":"10.1109/intellisys.2017.8324243","title":"A comparative study of the optimal control design using evolutionary algorithms: Application on a close-loop system","year":2017,"lang":"en","type":"article","venue":"2017 Intelligent Systems Conference (IntelliSys)","topic":"Adaptive Dynamic Programming Control","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Control theory (sociology); PID controller; Controller (irrigation); Linkage (software); Computer science; Evolutionary algorithm; Full state feedback; Stability (learning theory); Linear system; Optimal control; Control system; Open-loop controller; State (computer science); Control engineering; Algorithm; Control (management); Closed loop; Mathematics; Engineering; Mathematical optimization; Artificial intelligence; Temperature control","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":[0.001598827,0.0005761841,0.001087458,0.0002128915,0.001194808,0.0007484054,0.005265762,0.0002008384,0.000003203909],"category_scores_gemma":[0.0002249555,0.000431396,0.0002460254,0.0002228346,0.000433102,0.0006542196,0.0005927215,0.0004805765,0.0001268175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005931025,"about_ca_system_score_gemma":0.0004005828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001749098,"about_ca_topic_score_gemma":0.00004499016,"domain_scores_codex":[0.9946741,0.00122631,0.001179756,0.001139736,0.001145346,0.000634685],"domain_scores_gemma":[0.9921571,0.0005232553,0.002117199,0.003780656,0.001231802,0.000189994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001301028,0.005445157,0.007564276,0.0006756578,0.00315098,0.0001413398,0.02629825,0.3455139,0.006939028,0.5717441,0.0008051727,0.03042111],"study_design_scores_gemma":[0.0009009205,0.0006788958,0.0008716854,0.0005868482,0.0001078535,0.0000646835,0.004877682,0.9904724,0.000729375,0.0001187933,0.0001701298,0.0004207262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03301912,0.0002366893,0.9587336,0.00007556987,0.001555809,0.005586674,0.00003105303,0.0001787346,0.000582703],"genre_scores_gemma":[0.9947525,0.000005516359,0.004228168,0.00001511206,0.000162789,0.0005458934,0.000002157799,0.00002866807,0.0002591482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9617334,"threshold_uncertainty_score":0.9998138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.105194276679762,"score_gpt":0.3257999779399138,"score_spread":0.2206057012601518,"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."}}