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Model Predictive Control of a Wind Turbine Based on Linear
Parameter-Varying Models

Research Authors
Abdelrahman Morsi, Hossam S. Abbas, Abdelfatah M. Mohamed
Research Member
Research Department
Research Year
2015
Research Journal
2015 IEEE Conference on Control Applications (CCA)
Part of 2015 IEEE Multi-Conference on Systems and Control
Research Publisher
NULL
Research Vol
NULL
Research Rank
3
Research_Pages
pp. 318-323
Research Website
NULL
Research Abstract

This paper demonstrates the application of a
low conservative model predictive control (MPC) scheme
based on linear parameter-varying (LPV) models to
control a utility scale wind turbine. The main objective of
the controller is to allow the wind turbine to extract from
the wind a prespecified desired amount of power
according to the wind speed and to guarantee the stability
of the closed-loop system during the whole range of
operation. An LPV representation for a nonlinear model
of a 225 KW wind turbine is developed using the Jacobian
linearization based technique. A tight parameter set is
considered to reduce the conservatism of the LPV model.
Then a quasi min-max MPC-LPV algorithm is used to
compute online the optimal control input at each sampling
instant. The performance and the efficiency of the MPCLPV
scheme is validated via simulation and it is compared
with another MPC scheme based on linearized models of
the system.