A multi-observer based estimation framework for nonlinear systems under sensor attacks

Tianci Yang; Carlos Murguia; Margreta Kuijper; Dragan Nešić

doi:10.1016/j.automatica.2020.109043

A multi-observer based estimation framework for nonlinear systems under sensor attacks

Tianci Yang (Corresponding author), Carlos Murguia, Margreta Kuijper, Dragan Nešić

Research output: Contribution to journal › Article › Academic › peer-review

7 Citations (Scopus)

Abstract

For general discrete-time nonlinear systems, we address the state estimation problem under sensor attacks. We provide a general estimation scheme, built around the idea of sensor redundancy and multi-observers, capable of reconstructing the system state in spite of sensor attacks and noise, for a large class of nonlinear plants and observers. This scheme has been proposed by others for linear systems and here we propose a unifying framework for a much larger class of nonlinear systems.

Original language	English
Article number	109043
Number of pages	4
Journal	Automatica
Volume	119
DOIs	https://doi.org/10.1016/j.automatica.2020.109043
Publication status	Published - Sept 2020

Keywords

Cyber–physical systems
Multi-observer
Nonlinear observers
Security
Sensor attacks

Access to Document

10.1016/j.automatica.2020.109043

Cite this

@article{6a73eb440ce44b37be1f2c26f0846756,

title = "A multi-observer based estimation framework for nonlinear systems under sensor attacks",

abstract = "For general discrete-time nonlinear systems, we address the state estimation problem under sensor attacks. We provide a general estimation scheme, built around the idea of sensor redundancy and multi-observers, capable of reconstructing the system state in spite of sensor attacks and noise, for a large class of nonlinear plants and observers. This scheme has been proposed by others for linear systems and here we propose a unifying framework for a much larger class of nonlinear systems.",

keywords = "Cyber–physical systems, Multi-observer, Nonlinear observers, Security, Sensor attacks",

author = "Tianci Yang and Carlos Murguia and Margreta Kuijper and Dragan Ne{\v s}i{\'c}",

year = "2020",

month = sep,

doi = "10.1016/j.automatica.2020.109043",

language = "English",

volume = "119",

journal = "Automatica",

issn = "0005-1098",

publisher = "Elsevier",

}

TY - JOUR

T1 - A multi-observer based estimation framework for nonlinear systems under sensor attacks

AU - Yang, Tianci

AU - Murguia, Carlos

AU - Kuijper, Margreta

AU - Nešić, Dragan

PY - 2020/9

Y1 - 2020/9

N2 - For general discrete-time nonlinear systems, we address the state estimation problem under sensor attacks. We provide a general estimation scheme, built around the idea of sensor redundancy and multi-observers, capable of reconstructing the system state in spite of sensor attacks and noise, for a large class of nonlinear plants and observers. This scheme has been proposed by others for linear systems and here we propose a unifying framework for a much larger class of nonlinear systems.

AB - For general discrete-time nonlinear systems, we address the state estimation problem under sensor attacks. We provide a general estimation scheme, built around the idea of sensor redundancy and multi-observers, capable of reconstructing the system state in spite of sensor attacks and noise, for a large class of nonlinear plants and observers. This scheme has been proposed by others for linear systems and here we propose a unifying framework for a much larger class of nonlinear systems.

KW - Cyber–physical systems

KW - Multi-observer

KW - Nonlinear observers

KW - Security

KW - Sensor attacks

UR - http://www.scopus.com/inward/record.url?scp=85086410672&partnerID=8YFLogxK

U2 - 10.1016/j.automatica.2020.109043

DO - 10.1016/j.automatica.2020.109043

M3 - Article

AN - SCOPUS:85086410672

SN - 0005-1098

VL - 119

JO - Automatica

JF - Automatica

M1 - 109043

ER -

A multi-observer based estimation framework for nonlinear systems under sensor attacks

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this