We address the problem of state estimation, attack isolation, and control of discrete-time linear time-invariant systems under (potentially unbounded) actuator and sensor false data injection attacks. Using a bank of unknown input observers, each observer leading to an exponentially stable estimation error (in the attack-free case), we propose an observer-based estimator that provides exponential estimates of the system state despite actuator and sensor attacks. Exploiting sensor and actuator redundancy, the estimation scheme is guaranteed to work if a sufficiently small subset of sensors and actuators is under attack. Using the proposed estimator, we provide tools for reconstructing and isolating actuator and sensor attacks, and a control scheme capable of stabilizing the closed-loop dynamics by switching off isolated actuators. Simulation results are presented to illustrate the performance of our tools.

中文翻译：

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对抗性攻击下的未知输入多观察者估计和控制方法


我们解决了在（可能无界）执行器和传感器错误数据注入攻击下离散时间线性时不变系统的状态估计、攻击隔离和控制问题。使用一组未知的输入观测器，每个观测器都会导致指数稳定的估计误差（在无攻击的情况下），我们提出了一种基于观测器的估计器，尽管执行器和传感器受到攻击，它仍然可以提供系统状态的指数估计。利用传感器和执行器冗余，如果传感器和执行器的足够小的子集受到攻击，则保证估计方案起作用。使用所提出的估计器，我们提供了用于重建和隔离执行器和传感器攻击的工具，以及能够通过关闭隔离执行器来稳定闭环动态的控制方案。仿真结果旨在说明我们工具的性能。