{"id":"W4388919005","doi":"10.1016/j.ifacol.2023.10.1293","title":"Controller Design for Game Theoretic Steady-State Control: An LMI Approach","year":2023,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Extremum Seeking Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Control theory (sociology); Diagonal; Nash equilibrium; Controller (irrigation); Set (abstract data type); Constant (computer programming); Stability (learning theory); Computer science; State (computer science); Exponential stability; Argument (complex analysis); Mathematical optimization; Mathematics; Control (management); Nonlinear system; Algorithm","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":[0.001264626,0.001196811,0.0009225823,0.000481945,0.0004460714,0.001382535,0.00122286,0.001216617,0.004485277],"category_scores_gemma":[0.001664629,0.0003956085,0.0005645162,0.0004400054,0.0013318,0.0007969045,0.001180778,0.001614828,0.0007654798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001110793,"about_ca_system_score_gemma":0.001190956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00167892,"about_ca_topic_score_gemma":0.001596578,"domain_scores_codex":[0.9995227,0.0001869116,0.00002112834,0.00008864065,0.0001300171,0.00005070234],"domain_scores_gemma":[0.999492,0.0002646901,0.00007255269,0.00002914357,0.0001212627,0.0000202096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003373937,0.00005435392,0.000134091,0.0002393551,0.00004099243,0.0001240153,0.0001599342,0.8495962,0.004721444,0.1175171,0.001944034,0.02543471],"study_design_scores_gemma":[0.00001551796,0.00005645709,0.00004248024,0.00002151133,0.0000085915,0.00002112835,0.00002177072,0.9759547,0.0007891376,0.02120238,0.001857977,0.000008393326],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001556961,0.0001398048,0.9911503,0.0002157566,0.00003482288,0.00004833936,0.00002256155,0.000092022,0.006739512],"genre_scores_gemma":[0.7482018,0.001060715,0.2375542,0.0006244521,0.0002159764,0.001289775,0.0001341663,0.0001324492,0.01078654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004485277,"threshold_uncertainty_score":0.01500475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02523098932539463,"score_gpt":0.2396421904324185,"score_spread":0.2144112011070239,"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."}}