Input reconstruction for networked control systems subject to deception attacks and data losses on control signals

Jean-Yves Keller (1) , Karim Chabir (1) , Dominique Sauter (1)

1 CRAN - Centre de Recherche en Automatique de Nancy

State estimation of stochastic discrete-time linear systems subject to unknown inputs or constant biases has been widely studied but no work has been dedicated to the case where a disturbance switches between unknown input and constant bias. We show that such disturbance can affect a networked control system subject to deception attacks and data losses on the control signals transmitted by the controller to the plant. This paper proposes to estimate the switching disturbance from an augmented state version of the intermittent unknown input Kalman filter recently developed by the authors. Sufficient stochastic stability conditions are established when the arrival binary sequence of data losses follows a Bernoulli randomprocess.

Mots clés: cyber attacks; intermittent unknown inputs; Kalman filter

Domaines: Sciences de l'ingénieur [physics]; Automatique / Robotique

Jean-Yves Keller, Karim Chabir, Dominique Sauter. Input reconstruction for networked control systems subject to deception attacks and data losses on control signals. International Journal of Systems Science, 2016, 47 (4), pp.814-820. ⟨10.1080/00207721.2014.906683⟩. ⟨hal-01094322⟩