{"id":"W3122647070","doi":"10.1109/sta50679.2020.9329299","title":"Takagi-Sugeno fuzzy control for Multi-input Multi-output systems based on subspace state space identification","year":2020,"lang":"en","type":"article","venue":"","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Subspace topology; Identification (biology); Control theory (sociology); Fuzzy control system; System identification; Process (computing); Computer science; State space; State (computer science); Algorithm; State-space representation; Fidelity; Multivariable calculus; Fuzzy logic; Mathematics; Control (management); Artificial intelligence; Data modeling; Engineering; Control 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007582819,0.0003804267,0.0005548538,0.000116108,0.0002444785,0.000621505,0.001170002,0.0001355892,0.000002346332],"category_scores_gemma":[0.0002556544,0.0003168932,0.00022239,0.0003990885,0.00004691814,0.000389286,0.00006851777,0.0001651516,0.0003778861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001120641,"about_ca_system_score_gemma":0.000150762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002270877,"about_ca_topic_score_gemma":0.00003546604,"domain_scores_codex":[0.9968591,0.0002885478,0.0006408523,0.00104354,0.0005494882,0.0006184346],"domain_scores_gemma":[0.9976146,0.0003452186,0.0003881336,0.0008965302,0.0003629043,0.0003926523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00174832,0.002867313,0.006933346,0.002085458,0.0007793728,0.0002134045,0.007785121,0.382455,0.1052037,0.4135287,0.05387639,0.02252392],"study_design_scores_gemma":[0.005680447,0.0003575657,0.001158889,0.00003493304,0.00002198813,0.000002639748,0.0001273807,0.9876433,0.000601586,0.00007700137,0.003884275,0.0004099919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009691652,0.0002754229,0.9856398,0.007569374,0.001047743,0.00250245,0.00006112746,0.0006613901,0.001273543],"genre_scores_gemma":[0.9742459,0.000004741566,0.01919059,0.002115696,0.0002111031,0.0004441381,0.00001442584,0.00003638223,0.003737028],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9732767,"threshold_uncertainty_score":0.9999283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04729308469433932,"score_gpt":0.255971515415626,"score_spread":0.2086784307212866,"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."}}