网络物理系统中非线性估计的可否定性

IF 2.4 Q2 AUTOMATION & CONTROL SYSTEMS IEEE Control Systems Letters Pub Date : 2024-10-07 DOI:10.1109/LCSYS.2024.3473789
Camilla Fioravanti;Stefano Panzieri;Gabriele Oliva
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引用次数: 0

摘要

这封信介绍了一种新颖的全分布式有向强连接图非线性连续时间动力学估算方案。利用局部可否定性假设,尽管动态存在非线性依赖性,所提出的方法仍能对网络物理系统中相互依赖的子系统进行估计。这就将每个代理进行非线性状态估计的复杂任务转化为更易于管理的局部可否定性问题,以便设计估计增益。该方法的一个关键方面是,每个代理都应了解表征动态特性的整体非线性函数的 Lipschitz 常量的上限。面对这一问题,我们开发了一种新颖的分布式方法,从系统非线性的局部观测出发,估计全局的 Lipschitz 常数。我们通过模拟数值证明了所提方案的有效性。
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Negativizability for Nonlinear Estimation in Cyber–Physical Systems
This letter introduces a novel fully distributed estimation scheme for nonlinear continuous-time dynamics over directed and strongly connected graphs. Leveraging on the assumption of local negativizability, the proposed approach performs the estimation of the interdependent subsystems of a cyber-physical system, despite the presence of nonlinear dependencies on the dynamics. This transforms the intricate task of nonlinear state estimation by each agent into more manageable local negativizability problems for the design of the estimation gains. A pivotal aspect of the approach is that each agent should be aware of an upper bound on the Lipschitz constant of the overall nonlinear function that characterizes the dynamics. To face this issue, we developed a novel distributed methodology for the estimation of the global Lipschitz constant, starting from the local observations of the system’s nonlinearities. The effectiveness of the proposed scheme is numerically demonstrated through simulations.
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来源期刊
IEEE Control Systems Letters
IEEE Control Systems Letters Mathematics-Control and Optimization
CiteScore
4.40
自引率
13.30%
发文量
471
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