Data-Driven Unknown-Input Observers and State Estimation
Data-Driven Unknown-Input Observers and State Estimation
复制标题
数据驱动的未知输入观察者和状态估计
DOI：
10.1109/lcsys.2021.3102821
复制
发表时间：
2021
影响因子：
3
通讯作者：
G. Ferrari
中科院分区：
文献类型：
--
作者：
M. Turan;G. Ferrari
未知输入观测器（UIO）允许在不知道所有输入的情况下估计LTI系统的状态。在这封信中，我们提供了一个新的数据驱动的UIO基于行为系统理论和由Jan Willems及其同事提出的被称为基本引理的结果。我们从系统中收集的数据，提供渐近收敛的状态估计的UIO的存在的必要和充分条件，并提出了一个纯粹的数据驱动的算法计算。即使我们专注于UIO，我们的结果也适用于完全已知输入的标准情况。作为一个例子，我们将所提出的方法应用于分布式状态估计在直流微电网。
Unknown-input observers (UIOs) allow for estimation of the states of an LTI system without knowledge of all inputs. In this letter, we provide a novel data-driven UIO based on behavioral system theory and the result known as Fundamental Lemma proposed by Jan Willems and coworkers. We give necessary and sufficient conditions on the data collected from the system for the existence of a UIO providing asymptotically converging state estimates, and propose a purely data-driven algorithm for their computation. Even though we focus on UIOs, our results also apply to the standard case of completely known inputs. As an example, we apply the proposed method to distributed state estimation in DC microgrids.