{"id":"W2120609681","doi":"10.1109/tnn.2009.2016959","title":"Adaptive Neural Control for a Class of Nonlinear Systems With Uncertain Hysteresis Inputs and Time-Varying State Delays","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Networks","topic":"Piezoelectric Actuators and Control","field":"Engineering","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Control theory (sociology); Nonlinear system; Hysteresis; Bounded function; Adaptive control; Representation (politics); Artificial neural network; Lyapunov function; Backstepping; Class (philosophy); Computer science; Mathematics; State variable; Control (management); Artificial intelligence; Mathematical analysis","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":[],"consensus_categories":[],"category_scores_codex":[0.00007457894,0.0002552417,0.0004031551,0.0001017137,0.0001040759,0.00003990596,0.000096009,0.00009827328,0.000002281793],"category_scores_gemma":[0.000001327198,0.0002133958,0.00009124122,0.0002098984,0.00003225953,0.000150311,3.414606e-7,0.0002762241,6.55753e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004534447,"about_ca_system_score_gemma":0.00001268066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001921827,"about_ca_topic_score_gemma":0.00001291222,"domain_scores_codex":[0.9989201,0.00004345228,0.0003025632,0.0002199042,0.0001360304,0.0003779781],"domain_scores_gemma":[0.9993494,0.0002445427,0.00007099579,0.0001563752,0.00006768607,0.0001110682],"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":[0.0006576618,0.00003160604,0.000005557414,0.00001973544,0.0001182165,0.00000636395,0.00004232139,0.919151,0.000365239,0.000004020359,0.00004552863,0.07955273],"study_design_scores_gemma":[0.001905905,0.00105239,0.00001522556,0.00005378942,0.0001161363,0.00002321324,0.0000080819,0.9963604,0.0002170868,0.000009138587,0.00002029002,0.0002183528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08865035,0.0003737212,0.9097765,0.00007433842,0.0001759287,0.000687134,0.000080454,0.0001435418,0.00003805525],"genre_scores_gemma":[0.9993346,0.00003723833,0.0002251825,0.0001625365,0.00008248133,0.00007183255,0.000003237726,0.00003730362,0.00004560584],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9106842,"threshold_uncertainty_score":0.8702027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00745446442514979,"score_gpt":0.1944398523086453,"score_spread":0.1869853878834955,"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."}}