Robust Fault-tolerant Fuzzy Filtering with Exponential Time-varying Gains for Sampled-data T-S Fuzzy Systems

This paper proposes a novel approach to designing a fault-tolerant \({H}_{\infty }\) sampled-data fuzzy filter using exponential time-varying gains. The utilization of exponential time-varying gains not only achieves a reduction in convergence time but also provides relaxation in the numerical optimization of design conditions. Also, through the use of a robust control technique, the designed filter is equipped with enhanced fault-tolerant capabilities. In addition, sufficient conditions for ensuring \({H}_{\infty }\)-based state estimation performance are derived as linear matrix inequalities (LMIs) based on the Lyapunov–Krasovskii functional (LKF). Finally, simulation results demonstrate the superior performance of the proposed method when compared to existing methodologies.