Fixed-Time Adaptive Fuzzy Fault Estimation for Discrete-Time Systems With Digital Communication Networks

This paper investigates a novel fixed-time adaptive fault estimation (FE) scheme for discrete-time nonlinear systems operating over digital communication networks. To explicitly address communication capacity limitations, quantized measurement signals are incorporated into the adaptive laws, replacing the conventional assumption of real-valued output measurements. A discrete-time adaptive observer is then developed, for the first time, to achieve fixed-time fault reconstruction, ensuring rapid convergence while effectively compensating for quantization-induced errors. Furthermore, to cope with nonlinear uncertainties, an adaptive fuzzy approximation technique driven by quantized measurements is integrated into the proposed framework, thereby enhancing the robustness of the FE process. Finally, the effectiveness and advantages of the proposed method are demonstrated through simulation studies on a Boeing 747 aircraft dynamics model and a circuit model.