{"id":"W3191637487","doi":"10.1109/tcsi.2021.3098830","title":"Adaptive Fuzzy Fast Finite-Time Dynamic Surface Tracking Control for Nonlinear Systems","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems I Regular Papers","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":150,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Department of Education of Liaoning Province; National Natural Science Foundation of China","keywords":"Backstepping; Control theory (sociology); Tracking error; Fuzzy logic; Nonlinear system; Convergence (economics); Fuzzy control system; Adaptive control; Computer science; Tracking (education); Mathematics; Control (management); Artificial intelligence","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":[0.0004739569,0.0005328951,0.0009840898,0.0001509773,0.0003261699,0.0002515484,0.0001822405,0.0003442932,0.00001363459],"category_scores_gemma":[0.00003213298,0.0005423513,0.000319508,0.0002808613,0.00008653249,0.0002297366,0.000001309141,0.0003534277,0.00004963982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002605287,"about_ca_system_score_gemma":0.0001149975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003005085,"about_ca_topic_score_gemma":0.00004914604,"domain_scores_codex":[0.9972885,0.0002467861,0.0007748547,0.0006413744,0.0004275665,0.0006209412],"domain_scores_gemma":[0.997923,0.0007528021,0.0001416053,0.0005042866,0.0003518371,0.0003264811],"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":[0.00004355277,0.00007378556,0.000004513097,0.000443966,0.0008076978,0.00005305517,0.000268057,0.9202813,0.07054774,0.0001122304,0.00008396841,0.007280127],"study_design_scores_gemma":[0.002729034,0.00020357,0.00002549218,0.0005498761,0.0002417655,0.0001771003,0.001659535,0.9866039,0.0008533478,0.000003749005,0.00629951,0.0006531327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01405158,0.006275694,0.9699301,0.00007067119,0.003591099,0.00204877,0.001830586,0.0005803315,0.001621128],"genre_scores_gemma":[0.9956966,0.0001179307,0.0001968591,0.00003561397,0.0002542425,0.0001831134,0.00003193321,0.000171716,0.003311965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.981645,"threshold_uncertainty_score":0.9997028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0143996562548432,"score_gpt":0.2135842741218987,"score_spread":0.1991846178670555,"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."}}