Evidence map›Paper›PMID 39686129›Full record

ArticleSensors (Basel, Switzerland)2024

Robust Distributed Observers for Simultaneous State and Fault Estimation over Sensor Networks.

Dingguo Liang, Yunxiao Ren, Yuezu Lv, Silong Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Dingguo LiangDepartment of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing 100871, China.
Yunxiao RenDepartment of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing 100871, China.
Yuezu LvAdvanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology, Beijing 100081, China.
Silong WangDeep Space Exploration Laboratory, Beijing 100195, China.

Funding

Beijing Nova Program 20230484481National Natural Science Foundation of China 62088101, 62273045, U2341213
6 · The paper itself

Abstract

This paper focuses on simultaneous estimation of states and faults for a linear time-invariant (LTI) system observed by sensor networks. Each sensor node is equipped with an observer, which uses only local measurements and local interaction with neighbors for monitoring. The observability of said observer is analyzed where non-local observability of a sensor node is required in terms of the system state and faults. The distributed observers present features of H∞ performance to constrain the influence of disturbances on the estimation errors, for which the global design condition is transformed into a linear matrix inequality (LMI). The LMI is proven to be solvable given collective observability of the system and a suitable H∞ performance index. Moreover, in the case that no disturbances exist, fully distributed observers with adaptive gains are designed to asymptotically estimate the states and faults without using any global information from the network. Finally, the effectiveness of the proposed methods is verified through case studies on a spacecraft's attitude control system.

Indexed as

distributed observersfault estimationH∞ performancesensor networksspacecraft attitude control

Identifiers

PMID39686129
PMCPMC11645054

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.