A new adaptive control strategy for a class of nonlinear system using RBF neuro-sliding-mode technique: application to SEIG wind turbine control system

DOI10.1080/00207179.2016.1213423zbMath1366.93293OpenAlexW2515518377MaRDI QIDQ5280291

Françoise Lamnabhi-Lagarrigue, Armel Simo Fotso, Godpromesse Kenné

Publication date: 20 July 2017

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179.2016.1213423

zbMATH Keywords

voltage regulationmaximum power point trackingRBF neural network controlPWM converter

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Nonlinear systems in control theory (93C10) Application models in control theory (93C95) Adaptive control/observation systems (93C40) Lyapunov and other classical stabilities (Lagrange, Poisson, (L^p, l^p), etc.) in control theory (93D05) Variable structure systems (93B12)

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