{"id":"W3186040439","doi":"10.1109/tsmc.2021.3094975","title":"Adaptive Fuzzy Control With Global Stability Guarantees for Unknown Strict-Feedback Systems Using Novel Integral Barrier Lyapunov Functions","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Systems","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Backstepping; A priori and a posteriori; Control theory (sociology); Fuzzy control system; Stability (learning theory); Fuzzy logic; Adaptive control; Controller (irrigation); Lyapunov stability; Lyapunov function; Computer science; Mathematics; Mathematical optimization; Control (management); Artificial intelligence; Nonlinear system; Machine learning","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":[0.0006731324,0.0008729133,0.001439754,0.000212355,0.0004291448,0.0005493427,0.0002687919,0.0004590919,0.000009513635],"category_scores_gemma":[0.00002163105,0.0007836104,0.0003128575,0.0006194934,0.000206151,0.0003191765,0.000004856281,0.0004756106,0.00002380489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008943889,"about_ca_system_score_gemma":0.0002654446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001054421,"about_ca_topic_score_gemma":0.0005790222,"domain_scores_codex":[0.9956936,0.0004089106,0.001355295,0.0009458304,0.0007191268,0.0008771835],"domain_scores_gemma":[0.9968772,0.0005262661,0.0003049896,0.0008272243,0.001030503,0.0004338346],"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":[0.0007116455,0.0003515187,0.0002944508,0.001502233,0.002070887,0.0000337113,0.0003825814,0.983885,0.007498704,0.00256101,0.0002241345,0.0004840881],"study_design_scores_gemma":[0.005848285,0.0006478005,0.0001448725,0.001341191,0.0007249311,0.0008002298,0.009442046,0.9727104,0.0002981602,0.000006577085,0.006924176,0.001111278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04199461,0.005199411,0.9376046,0.00001720353,0.00628442,0.003152126,0.003710154,0.0004799123,0.001557534],"genre_scores_gemma":[0.9964334,0.000038602,0.0007260703,0.0000145581,0.0006202451,0.000636781,0.00002598778,0.0001646545,0.001339734],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9544387,"threshold_uncertainty_score":0.9994615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02602653689155562,"score_gpt":0.221394312422528,"score_spread":0.1953677755309723,"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."}}