Provably Robust Verification of Dissipativity Properties from Data
Provably Robust Verification of Dissipativity Properties from Data
复制标题
从数据中可靠地验证耗散特性
DOI：
--
复制
发表时间：
2020
影响因子：
6.8
通讯作者：
F. Allgöwer
中科院分区：
文献类型：
--
作者：
Anne Koch;J. Berberich;F. Allgöwer
耗散性对于系统分析和控制器设计是非常有价值的。随着可用数据量的增加，因此，人们越来越感兴趣的是直接从（测量）轨迹确定耗散特性，而系统的显式模型仍未公开。然而，大多数现有的数据驱动的耗散性的方法，保证耗散性条件只在有限的时间范围内，并提供弱或没有保证的鲁棒性存在噪声。在这篇文章中，我们提出了一个框架，用于验证耗散性能的测量数据与理想的保证。我们首先考虑输入状态测量的情况下，我们提供计算有吸引力的条件下存在的过程噪声。我们将这种方法扩展到输入输出数据，其中类似的结果在无噪声的情况下，并最终提供的情况下，嘈杂的输入输出轨迹的结果。
Dissipativity properties have proven to be very valuable for systems analysis and controller design. With the rising amount of available data, there has, therefore, been an increasing interest in determining dissipativity properties from (measured) trajectories directly, while an explicit model of the system remains undisclosed. Most existing approaches for data-driven dissipativity, however, guarantee the dissipativity condition only over a finite-time horizon and provide weak or no guarantees on robustness in the presence of noise. In this article, we present a framework for verifying dissipativity properties from measured data with desirable guarantees. We first consider the case of input-state measurements, where we provide computationally attractive conditions in the presence of process noise. We extend this approach to input–output data, where similar results hold in the noise-free case, and finally provide results for the case of noisy input–output trajectories.