This paper is concerned with distributed data‐driven observer design problem. The existing data‐driven observers rely on a common assumption that all the information about the system, and the calculations based upon this information are centralized. Therefore the resulting algorithms cannot be applied to the distributed systems in which each local observer receives only a part of the output signal. On the other hand, traditional model‐based distributed state estimation methods generally assume that the processes are decomposed according to the known process models, while in data‐driven approaches there is no such information available. The main goal of this paper is to extend the centralized data‐driven observer design approach to the distributed framework. The stability of the proposed data‐driven distributed observer is also proved analytically. A quadruple‐tank process is simulated to demonstrate the performance of the proposed scheme.

中文翻译：

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线性时不变系统的分布式数据驱动观察器

本文涉及分布式数据驱动的观察器设计问题。现有的数据驱动的观察者基于一个共同的假设，即关于系统的所有信息以及基于该信息的计算都是集中的。因此，所得算法无法应用于每个本地观察者仅接收一部分输出信号的分布式系统。另一方面，传统的基于模型的分布式状态估计方法通常假定过程是根据已知的过程模型分解的，而在数据驱动的方法中则没有此类信息。本文的主要目标是将集中数据驱动的观察者设计方法扩展到分布式框架。所分析的数据驱动的分布式观测器的稳定性也得到了证明。