Gaussian framework for nonlinear state estimation with stochastic event-trigger and packet losses

IF 5.9 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica Pub Date : 2025-02-20 DOI:10.1016/j.automatica.2025.112220

Weijun Lv , Chang Liu , Yong Xu , Renquan Lu , Ling Shi

引用次数: 0

Abstract

Nonlinear state estimation with stochastic event-trigger and packet losses is studied in this paper. To handle the nonlinearity and the uncertainty of the available information, the recursive probability density functions (PDFs) are characterized as Gaussian. Then, an event-trigger and packet losses induced Gaussian filter (EPGF) and its Gaussian smoother (EPGS) are derived to develop a new Gaussian framework. This developed framework is an extension of the standard Gaussian one and suitable for both linear and nonlinear systems. The key to its implementation is calculating a series of integrals with the Gaussian weight form, which can be approximated by various numerical techniques. In addition, according to the rule of three-degree spherical-radial cubature, two specific filtering and smoothing algorithms of the proposed framework are presented. Finally, a numerical simulation illustrates the effectiveness of the developed scheme.

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具有随机事件触发和包丢失的非线性状态估计的高斯框架

研究了具有随机事件触发和包丢失的非线性状态估计问题。为了处理可用信息的非线性和不确定性，将递归概率密度函数（pdf）表征为高斯函数。然后，推导了事件触发和丢包诱导高斯滤波器（EPGF）及其高斯平滑器（EPGS），建立了一个新的高斯框架。该框架是标准高斯框架的扩展，适用于线性和非线性系统。其实现的关键是用高斯权值形式计算一系列积分，高斯权值形式可以用各种数值技术来近似。此外，根据三度球径向立方体的规则，给出了该框架的两种具体滤波和平滑算法。最后，通过数值仿真验证了所提方案的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Automatica 工程技术-工程：电子与电气

CiteScore

10.70

自引率

7.80%

发文量

617

审稿时长

5 months

期刊介绍： Automatica is a leading archival publication in the field of systems and control. The field encompasses today a broad set of areas and topics, and is thriving not only within itself but also in terms of its impact on other fields, such as communications, computers, biology, energy and economics. Since its inception in 1963, Automatica has kept abreast with the evolution of the field over the years, and has emerged as a leading publication driving the trends in the field. After being founded in 1963, Automatica became a journal of the International Federation of Automatic Control (IFAC) in 1969. It features a characteristic blend of theoretical and applied papers of archival, lasting value, reporting cutting edge research results by authors across the globe. It features articles in distinct categories, including regular, brief and survey papers, technical communiqués, correspondence items, as well as reviews on published books of interest to the readership. It occasionally publishes special issues on emerging new topics or established mature topics of interest to a broad audience. Automatica solicits original high-quality contributions in all the categories listed above, and in all areas of systems and control interpreted in a broad sense and evolving constantly. They may be submitted directly to a subject editor or to the Editor-in-Chief if not sure about the subject area. Editorial procedures in place assure careful, fair, and prompt handling of all submitted articles. Accepted papers appear in the journal in the shortest time feasible given production time constraints.