SciELO - Scientific Electronic Library Online

 
vol.14 issue2Generation and Optimization of Fuzzy Controllers Using the NEFCON ModelRadial Basis Functions for Phase Unwrapping author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Computación y Sistemas

On-line version ISSN 2007-9737Print version ISSN 1405-5546

Abstract

RICALDE, Luis J.; CRUZ, Braulio J.  and  SANCHEZ, Edgar N. High Order Recurrent Neural Control for Wind Turbine with a Permanent Magnet Synchronous Generator. Comp. y Sist. [online]. 2010, vol.14, n.2, pp.133-143. ISSN 2007-9737.

In this paper, an adaptive recurrent neural control scheme is applied to a wind turbine with permanent magnet synchronous generator. Due to the variable behavior of wind currents, the angular speed of the generator is required at a given value in order to extract the maximum available power. In order to develop this control structure, a high order recurrent neural network is used to model the turbine-generator model which is assumed as an unknown system; a learning law is obtained using the Lyapunov methodology. Then a control law, which stabilizes the reference tracking error dynamics, is developed using Control Lyapunov Functions. Via simulations, the control scheme is applied to maximum power operating point on a small wind turbine.

Keywords : Neural networks; Wind turbine; Permanent magnet synchronous generator; Maximum power control; Lyapunov methodology.

        · abstract in Spanish     · text in English

 

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License