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Local identification of sensor attack and distributed resilient state estimation for linear systems

  • IEEE Conference on Decision and Control, 2018
  • DOI: (to be updated)
  • Authors: Junsoo Kim, Jin Gyu Lee, Chanhwa Lee, Hyungbo Shim, Jin H. Seo
  • Abstract: This paper presents a distributed attack-resilient state estimation scheme for continuous-time linear systems having redundant sensors when some of them are corrupted by adversaries. We first design a distributed state observer so that individual observers from each of output measurements communicate with their neighbors and cooperate to recover the full state of the system. Then, the observers are partitioned into disjoint groups and local monitoring systems are designed for each of them. Even though the system is not observable from measurements in each group, every influential attack is detected and identified by local monitors using only local information and local observer estimates within the local group, with the help of sensing redundancy. In process of local attack identification, a notion of sensor attack identifiability is introduced which does not require observability. Finally, all corrupted output measurements are removed from the observer communication and the distributed resilient state estimation is achieved.
  • Presentation material: CDC2018_JunsooKim

Simulation file

  • requires MATLAB/Simulink, tested in MATLAB2016b
  • Download:¬† KimLeeLeeShimSeo
  • Run “parameter.m”, and then run “simulation.slx”.¬†Simulation result plots are available by running “plot_fig.m”.

Related Work

“Detection of sensor attack and resilient state estimation for uniformly observable nonlinear systems”
Junsoo Kim, Chanhwa Lee, Hyungbo Shim, Yongsoon Eun, and Jin H. Seo
IEEE Transactions on Automatic Control, 2018 (early access)

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