离散事件系统的高阶观测器和基于高阶状态估计的特性

Kuize Zhang, Xiaoguang Han, Alessandro Giua, Carla Seatzu
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摘要

基于状态估计的特性是过去三十年来通过标注有限状态自动机建模的离散事件系统的核心特性。大多数现有成果都是基于一个知道系统结构的单个代理,该代理可以观察事件子集,并根据系统结构和代理对系统的观察来估计系统的状态。用于进行状态估计和验证基于状态估计的属性的主要工具叫做 \emph{observer},它是最初由拉宾和斯科特于 1959 年提出的幂集构造,用于确定具有 $\varepsilon$ 过渡的非确定有限自动机。在本文中,我们考虑了有标记的有限状态自动机,将基于状态估计的属性从单一代理扩展到有限有序代理集,并基于原始观测器和我们的\emph{并发组合}将原始观测器扩展为\emph{高阶观测器}。因此,我们建立了一个基于状态估计的高阶属性的一般框架,也建立了一个验证这些属性的基本工具。这个一般框架包含许多基本属性,如基于状态的不透明性、临界可观测性、确定性、高阶不透明性等。此外,还讨论了可以更有效地进行验证的特殊情况。在我们的一般框架中,系统的结构对所有代理 $A_1,(点),A_n$ 都是公开的,每个代理 $A_i$ 都有自己的可观测事件集 $E_i$,此外还知道其前面代理的所有可观测事件,但只能观测自己的可观测事件。我们的高阶观察者的直观含义是,代理 $A_n$ 知道 $A_{n-1}$ 所知道的关于 $A_2$ 所知道的关于 $A_1$ 的系统状态估计。
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High-order observers and high-order state-estimation-based properties of discrete-event systems
State-estimation-based properties are central properties in discrete-event systems modeled by labeled finite-state automata studied over the past 3 decades. Most existing results are based on a single agent who knows the structure of a system and can observe a subset of events and estimate the system's state based on the system's structure and the agent's observation to the system. The main tool used to do state estimation and verify state-estimation-based properties is called \emph{observer} which is the powerset construction originally proposed by Rabin and Scott in 1959, used to determinize a nondeterministic finite automaton with $\varepsilon$-transitions. In this paper, we consider labeled finite-state automata, extend the state-estimation-based properties from a single agent to a finite ordered set of agents and also extend the original observer to \emph{high-order observer} based on the original observer and our \emph{concurrent composition}. As a result, a general framework on high-order state-estimation-based properties have been built and a basic tool has also been built to verify such properties. This general framework contains many basic properties as its members such as state-based opacity, critical observability, determinism, high-order opacity, etc. Special cases for which verification can be done more efficiently are also discussed. In our general framework, the system's structure is publicly known to all agents $A_1,\dots,A_n$, each agent $A_i$ has its own observable event set $E_i$, and additionally knows all its preceding agents' observable events but can only observe its own observable events. The intuitive meaning of our high-order observer is what agent $A_n$ knows about what $A_{n-1}$ knows about \dots what $A_2$ knows about $A_1$'s state estimate of the system.
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