Adaptive state estimation for cyber physical systems under sparse attacks

Zhang, Hao; Peng, Chen; Sun, Hongtao; Du, Dajun

doi:10.1177/0142331217730123

Cited by 9 publications

(6 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, security problem with regard to protection against cyber attacks has also attracted a lot of attention. [17][18][19] Generally speaking, there are two categories of cyber attacks that have been studied: denial-of-service (DoS) attacks 20,21 and deception attacks. [22][23][24] The former can be achieved by injecting a large number of unwanted signals in a short period of time to prevent the timely transmission of data, bringing the effect of disrupting system performance.…”

Section: Introductionmentioning

confidence: 99%

Leader‐following consensus of multiple uncertain Euler–Lagrange systems under denial‐of‐service attacks

Xiao

Zhan

et al. 2022

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

In this thesis, we investigate a novel problem of security performance and consensus of multiple uncertain Euler-Lagrange systems (ELSs) under denial-of-service (DoS) attacks. First, we address how to make the system still function properly when the communication channel is cut off with intermittent DOS attacks by means of an event-triggered mechanism. At the same time, due to the uncertainty of the system there, we introduce an exosystem to generate signals so that the global information can be observed normally by distributed observers. Then, ELSs can be consensus while still ensuring its security. Furthermore, on the basis of this adaptive distributed observer functioning in the system, the problem for multiple ELSs of leader-following consensus is solved by using the Lyapunov method and the deterministic equivalence principle.Finally, numerical simulations are carried out to demonstrate the effectiveness of the proposed strategies. K E Y W O R D Sdenial-of-service (DoS) attacks, event-triggered, leader-following consensus, multiple Euler-Lagrange systems (ELSs), sampled-data-based

show abstract

Section: Introductionmentioning

confidence: 99%

Leader‐following consensus of multiple uncertain Euler–Lagrange systems under denial‐of‐service attacks

Xiao

Zhan

et al. 2022

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…On the other hand, there are many sparse systems in life, resulting in that the sparse AFs are required to exploit these prior information. Thus, many sparse AFs have been proposed [36]- [43].…”

Section: Introductionmentioning

confidence: 99%

A Kernel-Width Adaption Diffusion Maximum Correntropy Algorithm

Guo

Bing

2020

IEEE Access

View full text Add to dashboard Cite

Impulsive noises are widely existing in various systems like noise cancellation system and wireless communication systems, where adaptive filtering (AF) is always employed to identify specific systems. Additionally, the impulsive noises will affect the performance for estimating these systems, resulting in slow convergence or worse identification accuracy. In this paper, a diffusion maximum correntropy criterion (DMCC) algorithm with adaption kernel width is proposed, denoting as DMCC adapt algorithm, to find out a solution for dynamically choosing the kernel width. The DMCC adapt algorithm chooses small kernel width at initial stage to improve its convergence speed rate, and uses large kernel width at completion stage to reduce its steady-state error. To render the proposed DMCC adapt algorithm suitable for sparse system identifications, the DMCC adapt algorithm based on proportional coefficient adjustment is realized and named as diffusion proportional maximum correntropy criterion (DPMCC adapt). The theoretical analysis and simulation results are presented to show that the DPMCC adapt and DMCC adapt algorithms have better convergence than the traditional diffusion AF algorithms under impulse noise and sparse systems. INDEX TERMS Adaptive kernel width, diffusion algorithm, impulse noise, maximum correntropy criterion, sparse system identification.

show abstract

Section: Introductionmentioning

confidence: 99%

A Kernel-Width Adaption Diffusion Maximum Correntropy Algorithm

Guo¹,

Ma²,

Li³

2020

Preprint

View full text Add to dashboard Cite

In this paper, a diffusion maximum correntropy criterion (DMCC) algorithm with adaption kernel width is proposed, denoting as DMCC$_{\rm adapt}$ algorithm, to find out a solution for dynamically choosing the kernel width. The DMCC$_{\rm adapt}$ algorithm chooses small kernel width at initial stage to improve its convergence speed rate, and uses large kernel width at completion stage to reduce its steady-state error. To render the proposed DMCC$_{\rm adapt}$ algorithm suitable for sparse system identifications, the DMCC$_{\rm adapt}$ algorithm based on proportional coefficient adjustment is realized and named as diffusion proportional maximum correntropy criterion (DPMCC$_{\rm adapt}$). The theoretical analysis and simulation results are presented to show that the DPMCC$_{\rm adapt}$ and DMCC$_{\rm adapt}$ algorithms have better convergence than the traditional diffusion AF algorithms under impulse noise and sparse systems.

show abstract

Adaptive state estimation for cyber physical systems under sparse attacks

Cited by 9 publications

References 23 publications

Leader‐following consensus of multiple uncertain Euler–Lagrange systems under denial‐of‐service attacks

Leader‐following consensus of multiple uncertain Euler–Lagrange systems under denial‐of‐service attacks

A Kernel-Width Adaption Diffusion Maximum Correntropy Algorithm

A Kernel-Width Adaption Diffusion Maximum Correntropy Algorithm

Contact Info

Product

Resources

About