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Model predictive control (MPC) of an unknown system that is modelled by Gaussian process (GP) techniques is studied. Using GP, the variances computed during the modelling and inference processes allow us to take model uncertainty into account. The main issue in using MPC to control systems modelled by GP is the propagation of such uncertainties within the control horizon. In this study, two approaches...
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