{"id":"W4407952093","doi":"10.1109/cdc56724.2024.10886093","title":"Nonlinear Control Allocation: A Learning Based Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Control (management); Nonlinear system; Artificial intelligence; Mathematical optimization; Mathematics; Physics","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":[0.0006676653,0.000571139,0.0006688123,0.0004338539,0.0003485031,0.0007213654,0.0009126198,0.0007408003,0.003252681],"category_scores_gemma":[0.001124779,0.0003021023,0.0003396293,0.0004295419,0.0007458915,0.0007702499,0.0008991071,0.0008061143,0.0004621809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006690335,"about_ca_system_score_gemma":0.0006547812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003356824,"about_ca_topic_score_gemma":0.002769261,"domain_scores_codex":[0.999698,0.00008442902,0.00001513261,0.00006760721,0.00009900676,0.00003580829],"domain_scores_gemma":[0.9996312,0.0001651615,0.00004955956,0.0000293197,0.0001083519,0.00001643629],"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":[0.00003690441,0.00004095603,0.0001849463,0.00006228359,0.00002016577,0.00003070937,0.00003617053,0.8982415,0.001620696,0.01321705,0.0006323736,0.08587633],"study_design_scores_gemma":[0.000001840426,0.00001192257,0.00002622468,0.000002740136,0.000001964804,0.000005667176,0.000002445049,0.9978695,0.0002114799,0.001520564,0.0003436197,0.000001989366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004003675,0.0002027075,0.9917361,0.00009418606,0.00002443962,0.00002306624,0.000007574384,0.00008208758,0.003826069],"genre_scores_gemma":[0.7757918,0.0007116998,0.2053605,0.000229525,0.0002183323,0.0002590237,0.00006696517,0.00009407343,0.01726812],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003356824,"threshold_uncertainty_score":0.0108813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004957691386488002,"score_gpt":0.1969372379420339,"score_spread":0.1919795465555459,"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."}}