网络非线性系统的状态估计与非周期性采样延迟测量。

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS ISA transactions Pub Date : 2025-01-01 DOI:10.1016/j.isatra.2024.11.029
Xincheng Zhuang, Yang Tian, Haoping Wang
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引用次数: 0

摘要

本文旨在研究网络非线性系统在非周期性采样延迟测量条件下的远程状态估计。为解决这一问题,本文设计了一种新颖的采样数据非非线性观测器(SNO)。所设计的观测器由两部分组成:第一部分是连续时间观测器,第二部分是辅助变量设计,用于连续补偿第一部分状态观测器的输出估计误差。该辅助变量的设计为采样延迟测量提供了一种新的补偿方案。通过基于轨迹的稳定性理论,证明了 SNNO 相对于系统和输出扰动的输入到状态稳定性。新的理论工具揭示了拟议 SNNO 的收敛速率与采样和延迟周期之间的关系。文中还给出了模拟结果以及与其他采样数据观测器的比较分析。
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State estimation of networked nonlinear systems with aperiodic sampled delayed measurement
This paper aims to study the remote state estimation of networked nonlinear systems subject to aperiodic sampled delayed measurement. A novel sampled-data non-affine nonlinear observer (SNNO) is designed to address this issue. The designed observer is composed of two parts: the first part is a continuous-time observer, and the second part is an auxiliary variable design that provides continuous compensation of output estimation errors for the first part’s state observer. The design of this auxiliary variable provides a new compensation scheme for sampled delayed measurement. The input-to-state stability of the SNNO with respect to the system and output disturbance is proved by means of trajectory-based stability theory. The new theoretical tool reveals the relationship between the convergence rate of the proposed SNNO and the sampling and delay periods. Simulations and comparative analyses with other sampled-data observers are given.
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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