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A Multi-Observer Based Optimal Control Method for Nonlinear Systems Under Sensor Attacks
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DOI：10.1109/TASE.2024.3466894.png)
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Abstract
En 中文
A multi-observer based optimal control method is presented for nonlinear continuous-time systems under sensor attacks. On the basis of the ideas of sensor redundancy and multi-observers, a neural network (NN) based multi-observer method is introduced to find the attack-free set of sensors in order to deal with the influences of sensor attacks. Then, the adaptive dynamic programming (ADP) method with critic NN approximation is developed by utilizing the correct state estimate. The properties of the multi-observer based ADP method are analyzed by utilizing the Lyapunov theory. Numerical analysis is conducted to show the efficiency of the presented method Note to Practitioners-In practical engineering, the communication networks may provide new access points for cyberattacks which try to degrade the system control performance because of the physical constraints. These cyberattacks can affect the quality of the system data transmission, which brings great challenges to the effective optimal control of systems. Aiming at the above problems, this paper designs a multi-observer based optimal control method for nonlinear continuous-time systems under sensor attacks. A neural network (NN) based multi-observer method is provided to find the attack-free set of sensors. Then, the adaptive dynamic programming (ADP) method is presented to realize the optimal control of systems based on the state estimate. Numerical analysis is given to show the correctness of the presented method.
Keywords:
Observers
Nonlinear systems
Optimal control
Artificial neural networks
Computer crime
Dynamic programming
Automation
Stacking
Security
Uncertainty
sensor attacks
cyber-physical security
multi-observer
adaptive dynamic programming (ADP)
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