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Direct adaptive control of wind energy conversion systems using Gaussian networks

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2 Author(s)
Mayosky, M.A. ; Dept. of Electron., La Plata Univ., Argentina ; Cancelo, G.I.E.

Grid connected wind energy conversion systems (WECS) present interesting control demands, due to the intrinsic nonlinear characteristics of windmills and electric generators. In this paper a direct adaptive control strategy for WECS control is proposed. It is based on the combination of two control actions: a radial basis function network-based adaptive controller, which drives the tracking error to zero with user specified dynamics, and a supervisory controller, based on crude bounds of the system's nonlinearities. The supervisory controller fires when the finite neural-network approximation properties cannot be guaranteed. The form of the supervisor control and the adaptation law for the neural controller are derived from a Lyapunov analysis of stability. The results are applied to a typical turbine/generator pair, showing the feasibility of the proposed solution

Published in:

Neural Networks, IEEE Transactions on  (Volume:10 ,  Issue: 4 )

Date of Publication:

Jul 1999

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