<abstract xmlns="http://www.w3.org/1999/xhtml"><p> State estimation of stochastic discrete-time linear systems subject to unknown inputs has been widely studied, but few works take into account disturbances switching between unknown inputs and constant biases. We show that such disturbances affect a networked control system subject to deception attacks on the control signals transmitted by the controller to the plant via unreliable networks. This paper proposes to estimate the switching disturbance from an augmented state version of the intermittent unknown input Kalman filter. The sufficient stochastic stability conditions of the obtained filter are established when the arrival binary sequence of data losses follows a Bernoulli random process.</p></abstract>

State estimation of stochastic discrete-time linear systems subject to unknown inputs has been widely studied, but few works take into account disturbances switching between unknown inputs and constant biases. We show that such disturbances affect a networked control system subject to deception attacks on the control signals transmitted by the controller to the plant via unreliable networks. This paper proposes to estimate the switching disturbance from an augmented state version of the intermittent unknown input Kalman filter. The sufficient stochastic stability conditions of the obtained filter are established when the arrival binary sequence of data losses follows a Bernoulli random process.

State Filtering for Networked Control Systems Subject to Switching Disturbances

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"State Filtering for Networked Control Systems Subject to Switching Disturbances"}

State estimation of stochastic discrete-time linear systems subject to unknown inputs has been widely studied, but few works take into account disturbances...

State Filtering for Networked Control Systems Subject to Switching Disturbances

Online veröffentlicht: 03. Okt. 2018

Seitenbereich: 473 - 482

Eingereicht: 20. Feb. 2017

Akzeptiert: 04. Apr. 2018

DOI: https://doi.org/10.2478/amcs-2018-0036

Schlüsselwörter
Kalman filter, unknown inputs, constant bias, switching disturbances, linear system, covariance matrix

© 2018 Karim Chabir, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

State Filtering for Networked Control Systems Subject to Switching Disturbances

Online veröffentlicht: 03. Okt. 2018

Seitenbereich: 473 - 482

Eingereicht: 20. Feb. 2017

Akzeptiert: 04. Apr. 2018

DOI: https://doi.org/10.2478/amcs-2018-0036

SchlüsselwörterKalman filter, unknown inputs, constant bias, switching disturbances, linear system, covariance matrix

© 2018 Karim Chabir, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Kalman filter, unknown inputs, constant bias, switching disturbances, linear system, covariance matrix