Abstract
In this paper, an adaptive integral sliding-mode control scheme is presented to cope with the false data injection actuator attacks on a class of disturbed cyber–physical systems. Considering the time-varying state-dependent actuator attacks can be parameterized in the form of a neural network, a filter operator is firstly introduced to identify the unknown weight vectors. Then, an integral sliding-mode function is utilized to develop the attack tolerant controller, which can compensate for the impacts of actuator attacks and external disturbance on system performance. By using the Lyapunov stability theory, the uniformly ultimately bounded result of system states, NN weight estimation errors and sliding motion can be obtained. Finally, the effectiveness of the proposed control theory is verified via a decoupled model of an F-18 aircraft.
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