{"id":"W1686172019","doi":"10.3390/a8030697","title":"Comparative Study of DE, PSO and GA for Position Domain PID Controller Tuning","year":2015,"lang":"en","type":"article","venue":"Algorithms","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"PID controller; Particle swarm optimization; Control theory (sociology); Position (finance); Computer science; Controller (irrigation); Nonlinear system; Differential evolution; Tracking (education); Premature convergence; Genetic algorithm; Convergence (economics); Domain (mathematical analysis); Evolutionary algorithm; Mathematics; Artificial intelligence; Algorithm; Control engineering; Engineering; Control (management); Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001177452,0.0005965527,0.0006862106,0.0009679027,0.0002808424,0.0008243824,0.000492872,0.000728254,0.0006615922],"category_scores_gemma":[0.003304396,0.0001913483,0.0003892365,0.0006725582,0.0002782129,0.0006216597,0.0003171594,0.0004811936,0.0001085691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003874872,"about_ca_system_score_gemma":0.000505169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003514283,"about_ca_topic_score_gemma":0.003040439,"domain_scores_codex":[0.9995152,0.0001088224,0.00004339466,0.00007266337,0.0002145357,0.00004535888],"domain_scores_gemma":[0.999042,0.0005681124,0.00007820284,0.00007004017,0.0002203085,0.00002127286],"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":[0.0003496298,0.00016821,0.004065526,0.0004405562,0.0001761488,0.0001794644,0.0001305131,0.6420227,0.01366166,0.008333167,0.0008743459,0.329598],"study_design_scores_gemma":[0.00002672565,0.0001695904,0.001777572,0.00002010484,0.00003832061,0.00009242513,0.00003787636,0.9890507,0.006432258,0.0007424894,0.001595601,0.00001629611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2961935,0.007700363,0.6701958,0.0003575163,0.0001652628,0.0001620599,0.00008493991,0.000998312,0.02414226],"genre_scores_gemma":[0.8689094,0.002172673,0.1257999,0.00007617121,0.00003301205,0.0001266867,0.00009615022,0.00006055173,0.002725473],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003514283,"threshold_uncertainty_score":0.006987691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02653216129225933,"score_gpt":0.2781023755583094,"score_spread":0.2515702142660501,"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."}}