Fuzzy adaptive secure tracking control against unknown false data injection attacks for uncertain nonlinear systems with input quantization

Highlights：

• In contrast to previous secure control methods proposed for linear systems, this paper investigates the problem of secure tracking control of nonstrict-feedback uncertain nonlinear systems. The proposed control algorithm ensures that the controlled systems are bounded in the presence of an unknown FDI attack. In contrast to the existing results, which proposed control algorithms only consider the control problem of nonlinear systems with input quantization and cannot guarantee the stability and robustness of the closed-loop system when the controlled systems are subject to an unknown FDI attack.

• The sensors attacks compensators are constructed to counteract the impact of the systems suffering from unknown FDI attacks. Meanwhile, by designing a new coordinate transformation, a fuzzy adaptive secure tracking control design algorithm exploiting the corrupted state variables is proposed, which ensures the stability and robustness of the systems. In addition, by introducing a first-order filter and the approximation properties of fuzzy logic systems, the problem of repeated differentiation of the virtual controllers and the issue of the algebraic-loop in the backstepping method are avoided.

• Different from the existing results, they consider the strict-feedback nonlinear systems. This paper studies the nonstrict-feedback form, which overcomes the problem of the algebraic-loop in virtual controllers. At the same time, this paper studies the tracking control problem, which is more complex than the stabilization problem studied in the existing results, which requires the output signal of the systems to track a given reference signal well. In addition, the presented control method avoids chattering in the quantized signal by introducing a hysteretic quantizer.