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Originalpublikation
Berberich, J.; Köhler, J.; Müller, M.A.; Allgöwer, F.: On the design of terminal ingredients for data-driven MPC. In: IFAC-PapersOnLine (IFAC Papers Online) 54 (2021), Nr. 6, S. 257-263. DOI: https://doi.org/10.1016/j.ifacol.2021.08.554
We present a model predictive control (MPC) scheme to control linear time-invariant systems using only measured input-output data and no model knowledge. The scheme includes a terminal cost and a terminal set constraint on an extended state containing past input-output values. We provide an explicit design procedure for the corresponding terminal ingredients that only uses measured input-output data. Further, we prove that the MPC scheme based on these terminal ingredients exponentially stabilizes the desired setpoint in closed loop. Finally, we illustrate the advantages over existing data-driven MPC approaches with a numerical example.