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We address the problem of robust state estimation of a class of discrete-time nonlinear systems with positive-slope nonlinearities when the sensors are corrupted by (potentially unbounded) attack signals and bounded measurement noise. We propose an observer-based estimator, using a bank of circle-criterion observers, which provides a robust estimate of the system state in spite of sensor attacks and measurement noise. We first consider the attack-free case where there is measurement noise and we provide a design method for a robust circle-criterion observer. Then, we consider the case when a sufficiently small subset of sensors are subject to attacks and all sensors are affected by measurement noise. We use our robust circle-criterion observer as the main ingredient in building an estimator that provides robust state estimation in this case. Finally, we propose an algorithm for isolating attacked sensors in the case of bounded measurement noise. We test this algorithm through simulations.
We address the problem of state estimation and attack isolation for general discrete-time nonlinear systems when sensors are corrupted by (potentially unbounded) attack signals. For a large class of nonlinear plants and observers, we provide a genera
We address the problem of attack detection and isolation for a class of discrete-time nonlinear systems under (potentially unbounded) sensor attacks and measurement noise. We consider the case when a subset of sensors is subject to additive false dat
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