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Data-driven Predictive Control for Continuous-time Linear Parameter Varying Systems with Application to Wind Turbine

Xiaosuo Luo
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."

Keyword : Continuous-time, data-driven approach, linear parameter varying systems, model predictive control,subspace identification.

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