控制与决策2024,Vol.39Issue(11) :3664-3672.DOI:10.13195/j.kzyjc.2023.1372

线性时不变系统的分布式固定时间观测器

Distributed fixed-time observers for linear time-invariant systems

张锬 吴怀宇 朱振华 郑秀娟 关治洪
控制与决策2024,Vol.39Issue(11) :3664-3672.DOI:10.13195/j.kzyjc.2023.1372

线性时不变系统的分布式固定时间观测器

Distributed fixed-time observers for linear time-invariant systems

张锬 1吴怀宇 1朱振华 1郑秀娟 1关治洪2
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作者信息

  • 1. 武汉科技大学冶金自动化与检测技术教育部工程研究中心,武汉 430081;武汉科技大学机器人与智能系统研究院,武汉 430081
  • 2. 华中科技大学人工智能与自动化学院,武汉 430074
  • 折叠

摘要

针对线性时不变系统的分布式状态估计问题,基于双极限加权齐次估计理论和可观测性分解方法提出一类分布式固定时间收敛观测器.首先,针对单输入单输出积分链式系统,使用双极限加权齐次性方法设计集中式固定时间观测器.然后,基于可观测性分解将线性时不变系统分为可观测和不可观测子系统,传感器网络中每个智能体以集中式观测器为基础,在固定时间内仅用系统输出测量值重构局部可观子状态,利用智能体间状态信息构造一致性算法在固定时间内估计出局部不可观测子状态,从而在固定时间内实现状态全知.不同于已有工作,所提出观测器不需要构造具体的李雅普诺夫函数即可给出收敛时间的显示表达式.最后,通过仿真实验验证所设计观测器的有效性.

Abstract

A class of distributed fixed-time convergent observers is designed based on the bi-limit weighted homogeneous approximation theory and observability decomposition for the distributed state estimation of linear time-invariant systems.Firstly,for a single-input-single-output integrating chain system,a centralized fixed-time observer is designed for the system using bi-limit weighted homogeneous estimation.Then,the linear time-invariant system is decomposed into observable and unobservable subsystems based on the observability decomposition.Each agent in the sensor network reconstructs local observable sub-states in a fixed time based on the centralized observer by using only the system output measurements,and then state information between the agents is used to construct a consistent algorithm to estimate the local unobservable sub-states in a fixed time,thus realizing state omniscience in a fixed time.Unlike previous works,this paper does not need to construct a specific Lyapunov function to give an expression for the convergence time.Finally,the effectiveness of the designed observer is verified by simulations.

关键词

分布式估计/线性系统/加权齐次性/固定时间观测器/可观测性分解/传感器网络

Key words

distributed estimation/linear systems/weighted homogeneity/fixed-time observer/observability decomposition/sensor networks

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出版年

2024
控制与决策
东北大学

控制与决策

CSTPCD北大核心
影响因子:1.227
ISSN:1001-0920
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