Adaptive security control of time-varying constraints nonlinear cyber-physical systems with false data injection attacks

JOURNAL OF CONTROL AND DECISION(2024)

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摘要
In this article, an adaptive security control scheme is presented for cyber-physical systems (CPSs) suffering from false data injection (FDI) attacks and time-varying state constraints. Firstly, an adaptive bound estimation mechanism is introduced in the backstepping control design to mitigate the effect of FDI attacks. Secondly, to solve the unknown sign time-varying state-feedback gains aroused by the FDI attacks, a type of Nussbaum function is employed in the adaptive security control. Then, by constructing a barrier Lyapunov function, it can be ensured that all signals of controlled system are bounded and the time-varying state constraints are not transgressed. Finally, the provided simulation examples demonstrate the effectiveness of the proposed controller.
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关键词
Neural networks,backstepping technology,false data injection (FDI) attacks,nonlinear cyber-physical systems controls
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