文章基本信息

标题：On the design of terminal ingredients for data-driven MPC
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作者：Julian Berberich ; Johannes Köhler ; Matthias A. Müller 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：6
页码：257-263
DOI：10.1016/j.ifacol.2021.08.554
语种：English
出版社：Elsevier
摘要：AbstractWe 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.