{"id":"W2343136382","doi":"10.1504/ijied.2015.076293","title":"A comparative study of MPC and optimised PID control","year":2015,"lang":"en","type":"article","venue":"International Journal of Industrial Electronics and Drives","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"PID controller; Model predictive control; Computer science; Materials science; Control (management); Control engineering; Engineering; Temperature control; 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":[0.0009194902,0.0004092576,0.000732745,0.0005571452,0.0002060587,0.001190009,0.0005714758,0.0007829485,0.0009650412],"category_scores_gemma":[0.003397741,0.000249397,0.0002959029,0.000577037,0.0004196301,0.000730543,0.0003330146,0.0007198941,0.0001721794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005275941,"about_ca_system_score_gemma":0.0004272588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002281398,"about_ca_topic_score_gemma":0.0009887179,"domain_scores_codex":[0.9988323,0.0002543818,0.00005604426,0.0001328835,0.0006617901,0.00006253918],"domain_scores_gemma":[0.9988172,0.0006662305,0.0001142138,0.0001133973,0.0002684766,0.00002054244],"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":[0.0007363458,0.00008897332,0.001465462,0.0005620623,0.0001089042,0.0001669972,0.00009762418,0.8586728,0.01582941,0.003746119,0.0004246998,0.1181006],"study_design_scores_gemma":[0.00003562469,0.0005161494,0.002988077,0.00004884605,0.00004163033,0.0001649149,0.00003812062,0.9752322,0.01702675,0.001138075,0.002738215,0.00003133415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3741492,0.01330418,0.5681431,0.0004547166,0.0002322924,0.0001584041,0.0001915669,0.002089154,0.04127745],"genre_scores_gemma":[0.9686401,0.000887845,0.02859025,0.00002820936,0.0000216533,0.00002732033,0.00007165909,0.00004622103,0.001686718],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002281398,"threshold_uncertainty_score":0.004862785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02876548082005124,"score_gpt":0.2731448071547895,"score_spread":0.2443793263347383,"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."}}