{"id":"W2026180654","doi":"10.1109/chicc.2006.4346915","title":"An MPC Approach to Networked Control Design","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Control theory (sociology); Model predictive control; Controller (irrigation); Networked control system; Actuator; Computer science; Linear matrix inequality; Linear system; Stability (learning theory); Control system; Control (management); Mathematical optimization; Mathematics; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.000108528,0.0001120803,0.0001424383,0.00004594942,0.00002918725,0.00003338422,0.00009759065,0.00005163101,0.00001283698],"category_scores_gemma":[0.000004781341,0.0001064471,0.00001984126,0.0001424589,0.000004491783,0.0001548328,0.000002814706,0.00004265328,0.00003656132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004728048,"about_ca_system_score_gemma":0.000003594637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002585791,"about_ca_topic_score_gemma":0.000005895792,"domain_scores_codex":[0.9993579,0.00003495812,0.0001685078,0.0001379723,0.0000822369,0.0002183714],"domain_scores_gemma":[0.9996602,0.00002788463,0.00001297002,0.0002025453,0.0000289563,0.00006742516],"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":[0.000008674026,0.00001329876,0.00003538067,0.00000357494,0.000007436449,3.761151e-7,0.00001079154,0.9929451,0.002476026,0.00155256,0.001923283,0.001023449],"study_design_scores_gemma":[0.0005272164,0.00002064777,0.000139417,0.000002518743,0.000006164006,0.000001701652,0.000009142199,0.9978337,0.0001762229,0.0001621333,0.0009809241,0.0001402676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002816522,0.00007618831,0.9594836,0.00001151898,0.0001015673,0.0004862852,0.000001112827,0.0007422045,0.03881586],"genre_scores_gemma":[0.8440349,5.894569e-7,0.1551967,0.0000613753,0.0002400575,0.00009116084,0.000008165232,0.00003345966,0.0003335754],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8437532,"threshold_uncertainty_score":0.4340786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005763871865732147,"score_gpt":0.1803249786093573,"score_spread":0.1745611067436251,"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."}}