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

作者：Luo, Xiaosuo^*

来源：International Journal of Control Automation and Systems, 2017, 15(2): 619-626.

DOI：10.1007/s12555-015-0480-6

• Continuous-time
• data-driven approach
• linear parameter varying systems
• model predictive control
• subspace identification

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.

• 出版日期2017-4
• 单位重庆大学