{"id":"W3107154565","doi":"10.18280/jesa.530507","title":"Improved Vector Control of a Counter-Rotating Wind Turbine System Using Adaptive Backstepping Sliding Mode","year":2020,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Backstepping; Control theory (sociology); Robustness (evolution); Parametric statistics; Turbine; Vector control; Sliding mode control; Lyapunov function; Lyapunov stability; Induction generator; Computer science; Doubly fed electric machine; Control engineering; Adaptive control; Engineering; Mathematics; Nonlinear system; Control (management); Physics; AC power; Induction motor","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008320245,0.0005708794,0.001430082,0.0002454991,0.0002685492,0.0003118205,0.0005207402,0.0001604345,0.00003018924],"category_scores_gemma":[0.0003674729,0.0005213745,0.0003836458,0.0005230882,0.000055676,0.0006850032,0.00007436672,0.0006558485,0.00002708995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006470566,"about_ca_system_score_gemma":0.0001297993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006491774,"about_ca_topic_score_gemma":0.000004625411,"domain_scores_codex":[0.9956485,0.0004842347,0.002069555,0.0003761252,0.0006862601,0.0007353461],"domain_scores_gemma":[0.997404,0.0003071674,0.001063562,0.000329918,0.0004649477,0.000430412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00017335,0.00003229612,0.001763325,0.003342722,0.0014218,0.0003475765,0.004679974,0.4854582,0.4933476,0.0004334452,0.0002142125,0.008785501],"study_design_scores_gemma":[0.002379385,0.0002574776,0.004937396,0.002218604,0.0002047149,0.0009865583,0.0009521255,0.9862207,0.001336863,0.0000124997,0.00003818276,0.0004554964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6970838,0.002307959,0.2969045,0.00006064538,0.001137032,0.0008781448,0.0001041781,0.0007175294,0.0008061911],"genre_scores_gemma":[0.9915104,0.000007004799,0.007061632,0.00004530758,0.001148392,0.000009961808,0.000002372669,0.000198562,0.00001638464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5007625,"threshold_uncertainty_score":0.9997238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02072069067551741,"score_gpt":0.2284997804924753,"score_spread":0.2077790898169579,"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."}}