- Forthcoming, IEEE Transactions on Automatic Control
- DOI: 10.1109/TAC.2018.2840819
- Authors: Junsoo Kim, Chanhwa Lee, Hyungbo Shim, Yongsoon Eun, and Jin H. Seo
- Abstract: This paper presents a detection algorithm for sensor attacks and a resilient state estimation scheme for a class of uniformly observable nonlinear systems. An adversary is supposed to corrupt a subset of sensors with the possibly unbounded signals, while the system has sensor redundancy. We design an individual high-gain observer for each measurement output so that only the observable portion of the system state is obtained. Then, a nonlinear error correcting problem is solved by collecting all the information from those partial observers and exploiting redundancy. A computationally efficient, on-line monitoring scheme is presented for attack detection. Based on the attack detection scheme, an algorithm for resilient state estimation is provided. The simulation results demonstrate the effectiveness of the proposed algorithm.
Simulation file
- requires MATLAB/Simulink, tested in MATLAB2016b
- Download: KimLeeShimEunSeoTAC
- Run “ParameterSetup.m”, and then run “simulink.slx”. Simulation result plots are available by running “plot_fig.m”.
Related Works
- The conference version of this paper has been presented in IEEE CDC, 2016.
“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
Proc. of 2016 IEEE 55th Conference on Decision and Control, pp. 1297-1302, IEEE, Las Vegas, NV, USA, 2016.
http://dx.doi.org/10.1109/CDC.2016.7798445Presentation material: CDC2016_JunsooKim
- A follow-up study for this work, which deals with `attack-resilient distributed state estimation’ for linear systems, will be presented at IEEE CDC, 2018.
In this paper, a distributed state observer is designed so that individual observers from each 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 attack-monitoring systems are designed for each of them. Even though the system is not observable from measurements in each group, every influential attack is identified in each group using only local measurements.
“Local Identification of Sensor Attack and Distributed Resilient State Estimation for Linear Systems”
Junsoo Kim, Jin Gyu Lee, Chanhwa Lee, Hyungbo Shim, and Jin H. Seo
Proc. of 2018 IEEE 57th Conference on Decision and Control, IEEE, Miami Beach, FL, USA, 2018. (Forthcoming)
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