Resilient Adaptive Fuzzy Observer-Based Sliding Control for Nonlinear Systems with Unpredictable Sensor Delays

This work investigates resilient control for uncertain nonlinear systems subject to unknown and unpredictable sensor delays. Conventional observer-based delay-compensation methods typically require known delay bounds or measurable timing information, which limits their applicability to strongly nonlinear dynamics. To address this issue, a resilient adaptive fuzzy observer-based sliding control (AFOSMC) framework is developed. A generalized nonlinear plant model is considered, and an adaptive fuzzy observer is constructed to estimate unmeasured states while explicitly decomposing the delayed measurement residual into estimation and delay components. A sliding-mode controller integrated with fuzzy approximation ensures robust tracking in the presence of modeling uncertainties and delay-induced distortions. A delay-dependent Lyapunov function with an integral term is derived, yielding explicit conditions that guarantee uniform ultimate boundedness (UUB) of all closed-loop signals. The proposed approach provides a unified and delay-resilient solution for nonlinear observer–controller co-design under unpredictable sensing delays. Simulations on a Duffing oscillator with a 0.15 s sensing delay show that the proposed AFOSMC model achieves a total tracking RMSE of 3.6×10−2, whereas a baseline sliding-mode controller without delay compensation becomes unstable after delay activation.