This paper presents an attack-resilient estimation scheme for uniformly observable nonlinear systems having redundant sensors when a subset of sensors is corrupted by adversaries. We first design an individual high-gain observer from each measurement output so that partial information of system state is obtained. Then, a nonlinear error correcting problem is formulated by collecting all the information from each partial observers and it can be solved by exploiting redundancy. For most of the time, a computationally efficient monitoring system is running and it detects every influential attacks. A simple switching logic explores another combination of output measurement to find a correct candidate only when a residual signal exceeds its threshold.
['Junsoo Kim', 'Chanhwa Lee', 'Hyungbo Shim', 'Yongsoon Eun', 'Jin H. Seo']
Detection of sensor attack and resilient state estimation for uniformly observable nonlinear systems