论文标题
线性系统中基于数据的传输稳定
Data-based Transfer Stabilization in Linear Systems
论文作者
论文摘要
我们提出了一个新颖的框架，用于将知识从一个系统（源）转移到为第二系统（目标）设计稳定控制器。我们的动机源于以下假设：可以从源系统中收集大量数据，而目标系统的数据很少。我们考虑从源系统收集的数据嘈杂且嘈杂的两个情况下。对于每种情况，通过利用从源系统收集的数据以及对两个系统的最大距离的先验知识，我们找到了一个合适且相对较小的紧凑型系统，其中包含实际目标系统，然后提供一个稳定紧凑型集合的控制器。特别是，可以通过求解一组线性基质不等式（LMI）来获得控制器。详细讨论了这些LMI的可行性。我们通过两个低阶和高阶系统的数值案例研究来补充理论发现。
We present a novel framework for transferring the knowledge from one system (source) to design a stabilizing controller for a second system (target). Our motivation stems from the hypothesis that abundant data can be collected from the source system, whereas the data from the target system is scarce. We consider both cases where data collected from the source system is noiseless and noisy. For each case, by leveraging the data collected from the source system and a priori knowledge on the maximum distance of the two systems, we find a suitable, and relatively small, compact set of systems that contains the actual target system, and then provide a controller that stabilizes the compact set. In particular, the controller can be obtained by solving a set of linear matrix inequalities (LMIs). Feasibility of those LMIs is discussed in details. We complement our theoretical findings by two numerical case studies of low-order and high-order systems.
