Sliding Mode Control for IT2 Fuzzy Systems Under Sensor Fault Estimation

This paper delves into the output feedback sliding mode control (SMC) problems in a class of Interval Type-2 (IT2) fuzzy systems affected by sensor faults. Firstly, a Markovian chain is employed to depict transmission channels vulnerable to stochastic deception attacks, providing a more accurate representation of the real-world scenario. Secondly, by leveraging historical estimates of fault signals, a novel learning-based observer integrated with a Saturation Function is proposed to reconstruct sensor faults. This observer incorporates a dynamic saturation level aimed at enhancing filtering performance. Subsequently, based on the estimated fault information, an output feedback SMC law is designed, and its finite-time boundedness is analyzed. Finally, the proposed approach and its associated theoretical findings are extended to an inverted pendulum model.