{"id":"W2038567491","doi":"10.1002/aic.14579","title":"Distributed lyapunov‐based model predictive control with neighbor‐to‐neighbor communication","year":2014,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Model predictive control; Nonlinear system; Computer science; Process (computing); Trajectory; State (computer science); Lyapunov function; Control (management); Sampling (signal processing); Control theory (sociology); Artificial intelligence; Algorithm; Physics","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":[0.0006041258,0.0008125551,0.0008899977,0.0002431751,0.0005952964,0.0007576314,0.001495082,0.0007439272,0.001296876],"category_scores_gemma":[0.001239276,0.0003527149,0.0003382895,0.0003634222,0.0007241996,0.0009245177,0.001061937,0.0008702112,0.00033284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005764051,"about_ca_system_score_gemma":0.0007608359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002346097,"about_ca_topic_score_gemma":0.002402761,"domain_scores_codex":[0.9995491,0.0001091684,0.00001828306,0.0001161066,0.0001655619,0.00004188517],"domain_scores_gemma":[0.9994755,0.0002162256,0.00008778548,0.00007201794,0.0001233702,0.00002507839],"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":[0.00009338433,0.00004709323,0.000249933,0.00005774013,0.00002693873,0.00007938292,0.00008134801,0.9568691,0.003165824,0.008186602,0.0004703841,0.03067238],"study_design_scores_gemma":[0.000008436492,0.00003497199,0.00003015171,0.000001623479,0.000002909441,0.000007140878,0.000004072011,0.9978389,0.0004770937,0.001376413,0.0002155868,0.000002798954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02740433,0.0002659968,0.9669287,0.0001260368,0.00005842951,0.00003543185,0.00001860705,0.0002378869,0.004924689],"genre_scores_gemma":[0.9681409,0.0001099481,0.02921731,0.00004474091,0.00003155987,0.00008400177,0.00003474398,0.00001928219,0.002317616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002346097,"threshold_uncertainty_score":0.004664898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003954539936165799,"score_gpt":0.1903791557920021,"score_spread":0.1864246158558363,"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."}}