{"id":"W2146544042","doi":"10.1016/j.ifacol.2015.08.146","title":"Adaptive Dynamic Surface Output-Feedback Control for a Class of Hysteric Nonlinear Systems with Prespeeified Tracking Performance","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Piezoelectric Actuators and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Backstepping; Control theory (sociology); Nonlinear system; Tracking error; Norm (philosophy); Computer science; Transformation (genetics); Observer (physics); Hysteresis; Tracking (education); Backlash; Scheme (mathematics); Artificial neural network; Adaptive control; Mathematics; Control (management); Artificial intelligence; Law","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":[0.0002786793,0.0003647515,0.0003622123,0.0001662371,0.000185911,0.0003535077,0.0005056518,0.0004363136,0.0006455508],"category_scores_gemma":[0.0004523639,0.0001067021,0.0002408373,0.00015901,0.0003901634,0.0003414142,0.0003065425,0.0004903523,0.000103143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002515835,"about_ca_system_score_gemma":0.0002814552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001955267,"about_ca_topic_score_gemma":0.001742852,"domain_scores_codex":[0.9998684,0.00001863867,0.000008672018,0.00003482955,0.00005110413,0.00001826415],"domain_scores_gemma":[0.9998154,0.00006460268,0.00003506583,0.00001760225,0.00005879853,0.0000086684],"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":[0.0002902296,0.0001145651,0.001591772,0.000496434,0.0000744496,0.0004465072,0.0004125643,0.585694,0.1385665,0.02455679,0.001580078,0.2461762],"study_design_scores_gemma":[0.000009076837,0.00005415158,0.0002652041,0.000004005104,0.0000045296,0.00002691331,0.000007990719,0.9952216,0.003137998,0.0005473767,0.0007166499,0.000004580826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04300256,0.0003558912,0.9541818,0.00007101961,0.00004422629,0.00002589455,0.0000116673,0.0001855277,0.002121423],"genre_scores_gemma":[0.9664612,0.0002791264,0.03079626,0.00003452009,0.0000305269,0.00005525108,0.0000352954,0.00001144288,0.002296424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001955267,"threshold_uncertainty_score":0.003887773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01595031673325092,"score_gpt":0.2077507186271243,"score_spread":0.1918004018938733,"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."}}