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We consider the problem of estimating signal attacks injected into the actuators or sensors of control systems, assuming the attack is detectable, i.e., it can be seen at the output. We show that there exists a trade-off between attack rejection and control, and that the estimator design depends on the controller used. We use dual rate sampling to enhance detectability of the attacks and we provide different methods to design the estimator. The first method is by solving a model matching problem subject to causality constraints. The second method exploits dual rate sampling to accurately reconstruct the unknown input. The third method is using a dual rate unknown input observer.We provide conditions on the existence of these estimators, and show that dual rate unknown input observers always exist if the multirate system does not have a zero at 1.
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A Multirate Adaptive Control for MIMO Systems with Application to Cyber-Physical Security
This paper proposes a multirate output-feedback controller for multi-input multi-output (MIMO) systems, possibly with non-minimum-phase zeros, using the L1 adaptive control structure. The analysis of stability and robustness of the sampled-data controller reveals that under certain conditions the performance of a continuous-time reference system is uniformly recovered as the sampling time goes to zero. The controller is designed for detection and mitigation of actuator attacks. By considering a multirate formulation, stealthy zero-dynamics attacks become detectable. The experimental results from the flight test of a small quadrotor are provided. The tests show that the multirate L1 controller can effectively detect the zero-dynamics actuator attack and recover stability of the quadrotor.
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- Award ID(s):
- 1739732
- PAR ID:
- 10099220
- Date Published:
- Journal Name:
- 2018 IEEE Conference on Decision and Control
- Page Range / eLocation ID:
- 6620 to 6625
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/CDC.2018.8619570
