Resilient Event-Triggered Observer-Based Control of Uncertain Nonlinear Fuzzy Systems Subject to Unknown Inputs
Mohsen Farbood, Zeinab Echreshavi, Saleh Mobayen, Paweł Skruch
Abstract
This paper proposes a novel observer-based event-triggered integral sliding mode control (SMC) strategy for Takagi-Sugeno fuzzy systems (TSFM) subject to unknown inputs, external disturbances, and model uncertainties. To ensure robust state estimation, a newly formulated unknown input observer (UIO) is developed that accommodates nonlinear output functions, thereby overcoming the limitations of existing methods that assume linear outputs. Additionally, a disturbance observer is introduced to estimate unmatched external disturbances effectively. Two fuzzy integral sliding surfaces are designed, a periodic-time surface to enhance robustness and a time-triggered surface to reduce computational burden and control signal chattering. An event-triggered mechanism based on a time-decaying threshold is incorporated to optimize control update instances, ensuring Zeno-free behavior. Lyapunov-based stability analysis confirms the ultimate boundedness stability (UBS) of the closed-loop system, and controller gains are computed through linear matrix inequalities (LMIs) and steady-state output theory. Simulation studies, including a numerical and practical truck-trailer system, validate the superior performance of the proposed control strategy in terms of disturbance rejection, reduced computation, and robustness compared to conventional methods.