Skip to main content
CenXiv.org
This website is in trial operation, support us!
We gratefully acknowledge support from all contributors.
Contribute
Donate
cenxiv logo > eess > arXiv:2507.18493

Help | Advanced Search

Electrical Engineering and Systems Science > Systems and Control

arXiv:2507.18493 (eess)
[Submitted on 24 Jul 2025 (v1) , last revised 31 Jul 2025 (this version, v2)]

Title: Global Observer Design for a Class of Linear Observed Systems on Groups

Title: 一类群上线性观测系统的全局观测器设计

Authors:Changwu Liu, Yuan Shen
Abstract: Linear observed systems on groups encode the geometry of a variety of practical state estimation problems. In this paper, we propose a unified observer framework for a class of linear observed systems by restricting a bi-invariant system on a Lie group to its normal subgroup. This structural property powerfully enables a system immersion of the original system into a linear time-varying system. Leveraging the immersion, an observer is constructed by first designing a Kalman-like observer for the immersed system and then reconstructing the group-valued state via optimization. Under a rank condition, global exponential stability (GES) is achieved provided one global optimum of the reconstruction optimization is found, reflecting the topological difficulties inherent to the non-Euclidean state space. Semi-global stability is guaranteed when input biases are jointly estimated. The theory is applied to the GES observer design for two-frame systems, capable of modeling a family of navigation problems. Two non-trivial examples are provided to illustrate implementation details.
Abstract: 线性观测系统在群上编码了各种实际状态估计问题的几何结构。 在本文中,我们通过将一个双不变系统限制在其正规子群上,提出了一类线性观测系统的统一观测器框架。 这种结构特性强有力地使得原系统能够浸入到一个时变线性系统中。 利用这种浸入,首先为浸入系统设计一个类似卡尔曼的观测器,然后通过优化重构群值状态。 在秩条件满足的情况下,只要找到重构优化的一个全局最优解,就可以实现全局指数稳定(GES),这反映了非欧几里得状态空间固有的拓扑困难。 当输入偏差被联合估计时,保证半全局稳定性。 该理论应用于两帧系统的GES观测器设计,能够对一类导航问题进行建模。 提供了两个非平凡的例子来说明实现细节。
Comments: 16 pages, 1 figure
Subjects: Systems and Control (eess.SY)
Cite as: arXiv:2507.18493 [eess.SY]
  (or arXiv:2507.18493v2 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2507.18493
arXiv-issued DOI via DataCite

Submission history

From: Changwu Liu [view email]
[v1] Thu, 24 Jul 2025 15:05:23 UTC (254 KB)
[v2] Thu, 31 Jul 2025 06:52:00 UTC (258 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled
  • View Chinese PDF
  • View PDF
  • HTML (experimental)
  • TeX Source
view license
Current browse context:
eess.SY
< prev   |   next >
new | recent | 2025-07
Change to browse by:
cs
cs.SY
eess

References & Citations

  • NASA ADS
  • Google Scholar
  • Semantic Scholar
a export BibTeX citation Loading...

BibTeX formatted citation

×
Data provided by:

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender (What is IArxiv?)
  • Author
  • Venue
  • Institution
  • Topic

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
  • About
  • Help
  • contact arXivClick here to contact arXiv Contact
  • subscribe to arXiv mailingsClick here to subscribe Subscribe
  • Copyright
  • Privacy Policy
  • Web Accessibility Assistance
  • arXiv Operational Status
    Get status notifications via email or slack

京ICP备2025123034号