|Data-driven Predictive Control for Continuous-time Linear Parameter Varying Systems with Application to Wind Turbine
International Journal of Control, Automation, and Systems, vol. 15, no. 2, pp.619-626, 2017
Abstract : "A new data-driven predictive control method based on subspace identification for continuous-time linear
parameter varying (LPV) systems is presented in this paper. It is developed by reformulating the continuous-time
LPV system which utilizes Laguerre filters to obtain the subspace prediction of output. The subspace predictors are
derived by QR decomposition of input-output and Laguerre matrices obtained by input-output data. The predictors
are then applied to design the model predictive controller. It is shown that the integrated action is incorporated in
the control effect to eliminate the steady-state offset. We control the continuous-time LPV systems to obtain the
attractive performance with the proposed data-driven predictive control method. The proposed controller is applied
to a wind turbine to verify its effectiveness and feasibility."
Continuous-time, data-driven approach, linear parameter varying systems, model predictive control,subspace identification.
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