论文标题
确定最佳输入输出属性：数据驱动的方法
Determining optimal input-output properties: A data-driven approach
论文作者
论文摘要
由于它们在系统分析和（鲁棒）控制器设计中的相关性，我们考虑了仅从数据中确定先验未知系统的控制理论系统属性的问题。更具体地说，我们为离散时间线性时间不变的系统引入了必要且充分的条件，以在有限的时间范围内满足给定的积分二次约束（IQC），仅使用有限长度的输入输出轨迹。此外，对于某些类别的IQC，我们提供了半决赛程序（SDP）形式的凸优化问题，以检索未知系统满足的最紧密的系统属性描述。最后，我们提供了有限和无限视野IQC之间差异的界限，并说明了所提出的方案在多种模拟研究中的有效性，包括噪声测量和高维系统。
Due to their relevance in systems analysis and (robust) controller design, we consider the problem of determining control-theoretic system properties of an a priori unknown system from data only. More specifically, we introduce a necessary and sufficient condition for a discrete-time linear time-invariant system to satisfy a given integral quadratic constraint (IQC) over a finite time horizon using only one input-output trajectory of finite length. Furthermore, for certain classes of IQCs, we provide convex optimization problems in form of semidefinite programs (SDPs) to retrieve the optimal, i.e. the tightest, system property description that is satisfied by the unknown system. Finally, we provide bounds on the difference between finite and infinite horizon IQCs and illustrate the effectiveness of the proposed scheme in a variety of simulation studies including noisy measurements and a high dimensional system.
