Adaptive switching T–S fuzzy observers for nonlinear systems under sparse sensor attacks

This paper investigates the secure state estimation problem of nonlinear cyber-physical systems (CPSs) subject to sparse sensor attacks. A novel adaptive T–S fuzzy observer is developed with adaptive switching mechanism. The switching mechanism implemented by introducing a switching function matrix ensures that the sensor data used for reconstructing the system state are reliable. A fuzzy performance index is proposed to drive the switching function matrix into the correct mode and truncate the attacked channels. It is shown that the observer can converge to a bounded neighbourhood of the origin system regardless of attack signals. The simulation of a nonlinear system illustrates the estimation performance of the proposed adaptive switching T–S fuzzy observer.