A fully distributed weight design approach to consensus Kalman filtering for sensor networks

Zhang, Ya; Tian, Yu‐Ping

doi:10.1016/j.automatica.2019.02.052

Cited by 57 publications

(16 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This completes the proof of the theorem.□ Remark 3 Distributed estimation is an important problem in MASs and has been widely investigated. In most of the existing works [25–27], unknown input is not considered in the target. For systems with unknown disturbances belonging to

l_{2} false[0, normal∞ false]

, distributed H

_{\infty}

observer is commonly used in literature to estimate the targets [28–30].…”

Section: Distributed Observermentioning

confidence: 99%

Distributed adaptive observer‐based output formation‐containment control for heterogeneous multi‐agent systems with unknown inputs

Zhang

Wen

Chen

et al. 2020

IET Control Theory & Appl

Self Cite

View full text Add to dashboard Cite

l_{2} false[0, normal∞ false]

, distributed H

_{\infty}

observer is commonly used in literature to estimate the targets [28–30].…”

Section: Distributed Observermentioning

confidence: 99%

Distributed adaptive observer‐based output formation‐containment control for heterogeneous multi‐agent systems with unknown inputs

Zhang

Wen

Chen

et al. 2020

IET Control Theory & Appl

Self Cite

View full text Add to dashboard Cite

“…With technical progress in sensing, communication and control domains, multi‐agent systems (MASs) have attracted an increasing number of attention from researchers 1‐5 . MASs have widespread applications in several areas, such as robot teams, 6 sensor networks, 7 and satellite clusters 8 . As a fundamental task of cooperative control, consensus for MASs have been widely studied in recent years and numerous consensus algorithms have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Secure consensus control for multi‐agent systems against attacks on actuators and sensors

Huo

Zhang

2022

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

This article studies the secure leader-following consensus control problem for discrete-time multi-agent systems under false data injection (FDI) attacks on both actuators and sensors. It is shown that under standard consensus protocol, an attacked follower can cause normal followers to fail to follow the leader if the normal followers can access the attacked follower through directed paths of arbitrary length. To mitigate the adverse impacts of FDI attacks, a secure observer-based consensus protocol is presented where local observer is used to estimate the system state and attack signal simultaneously and then the uniformly ultimately boundedness of state consensus error between all followers and leader can be guaranteed. Finally, a simulation example on the LC oscillator networks in the presence of FDI attacks validates the unavailability of standard consensus protocol and the effectiveness of the proposed secure observer-based consensus protocol.

show abstract

“…In order to further improve the detection performance of the fusion system, a series of new optimal fusion algorithms based on covariance, large deviation analysis, least square fusion rules, and Rao test [8][9][10][11][12] of the distributed detection fusion system are proposed. In recent years, many scholars have introduced a neural network [13], Kalman filter [14][15][16], and (generalized) likelihood ratio (GLRT) [17][18][19][20] into sensor systems to realize signal detection in various fields. All the above researches assume that the noise obeys a certain distribution and lack the research on chaotic noise background combined with phase space reconstruction.…”

Section: Introductionmentioning

confidence: 99%

Distributed Sensor Local Linear Fusion Detection of Weak Pulse Signal in Chaotic Background

Zhao

et al. 2021

Journal of Sensors

View full text Add to dashboard Cite

This paper combines the distributed sensor fusion system with the signal detection under chaotic noise to realize the distributed sensor fusion detection from chaotic background. First, based on the short-term predictability of the chaotic signal and its sensitivity to small interference, the phase space reconstruction of the observation signal of each sensor is carried out. Second, the distributed sensor local linear autoregressive (DS-LLAR) model is constructed to obtain the one-step prediction error of each sensor. Then, we construct a Bayesian risk model and also obtain the corresponding conditional probability density function under each sensor’s hypothesis test which firstly needs to fit the distribution of prediction errors according to the parameter estimation. Finally, the fusion optimization algorithm is designed based on the Bayesian fusion criterion, and the optimal decision rule of each sensor and the optimal fusion rule of the fusion center are jointly solved to effectively detect the weak pulse signal in the observation signal. Simulation experiments show that the proposed method which used a distributed sensor combined with a local linear model can effectively detect weak pulse signals from chaotic background.

show abstract

A fully distributed weight design approach to consensus Kalman filtering for sensor networks

Cited by 57 publications

References 24 publications

Distributed adaptive observer‐based output formation‐containment control for heterogeneous multi‐agent systems with unknown inputs

Distributed adaptive observer‐based output formation‐containment control for heterogeneous multi‐agent systems with unknown inputs

Secure consensus control for multi‐agent systems against attacks on actuators and sensors

Distributed Sensor Local Linear Fusion Detection of Weak Pulse Signal in Chaotic Background

Contact Info

Product

Resources

About