论文标题
关于显式数据驱动（M）PC的确定性观点
A deterministic view on explicit data-driven (M)PC
论文作者
论文摘要
我们表明，对于线性确定性系统，数据驱动的预测控制（DPC）的明确实现比以前认为的更可拖延。为此，我们比较了与确定性DPC和经典模型预测控制（MPC）相对应的最佳控制问题（OCP），指定其密切关系，并系统地消除DPC固有的歧义。作为中心结果，我们发现这些类型的DPC和MPC的明确解决方案的复杂性完全相同。我们用两个数字示例来说明我们的结果，突出了我们方法的特征。
We show that the explicit realization of data-driven predictive control (DPC) for linear deterministic systems is more tractable than previously thought. To this end, we compare the optimal control problems (OCP) corresponding to deterministic DPC and classical model predictive control (MPC), specify its close relation, and systematically eliminate ambiguity inherent in DPC. As a central result, we find that the explicit solutions to these types of DPC and MPC are of exactly the same complexity. We illustrate our results with two numerical examples highlighting features of our approach.
