This paper studies the problem of fuzzy adaptive secure tracking control for nonstrict-feedback nonlinear systems with unknown false data injection (FDI) attacks and input quantization. In the nonstrict-feedback nonlinear systems, the nonlinear functions contain all state variables so that the existing control methods will lead to the algebraic-loop problem. This difficulty is solved by combining the variable separation method and the properties of fuzzy basis functions. Furthermore, the tremor problem caused by the quantized input is solved by using the nonlinear function separation technique and the impact of FDI attacks is mitigated by constructing the attack compensators. On this basis, a secure tracking control strategy is proposed, which ensures the tracking error can converge to a small neighborhood of the origin and all signals of the closed-loop systems are bounded even in the presence of unknown FDI attacks. Different from the existing resilient control results for dealing with FDI attacks, this paper proposes a secure tracking control method of nonstrict-feedback nonlinear systems and also quantifies the input signal to reduce the signal transmission burden. Finally, the simulation results verify the effectiveness of the designed control algorithm.

本文研究了具有未知虚假数据注入（FDI）攻击和输入量化的非严格反馈非线性系统的模糊自适应安全跟踪控制问题。在非严格反馈非线性系统中，非线性函数包含所有状态变量，现有的控制方法会导致代数环问题。结合变量分离法和模糊基函数的性质，解决了这一难题。此外，利用非线性函数分离技术解决了量化输入引起的震颤问题，并通过构造攻击补偿器减轻了FDI攻击的影响。在此基础上，提出了一种安全的跟踪控制策略，这确保了跟踪误差可以收敛到原点的一个小邻域，并且即使在存在未知 FDI 攻击的情况下，闭环系统的所有信号也是有界的。与现有应对FDI攻击的弹性控制结果不同，本文提出了一种非严格反馈非线性系统的安全跟踪控制方法，并对输入信号进行量化，以减轻信号传输负担。最后，仿真结果验证了所设计控制算法的有效性。