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This is a Quantitative Study study.

September 24, 2025

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

Key Points

The proposed adaptive T–S fuzzy observer enables secure state estimation under sparse sensor attacks, allowing reliable data reconstruction.
A novel switching function matrix optimizes the performance index, ensuring the observer effectively handles attack signals.
The simulation shows that the observer converges to a bounded neighbourhood of the original system, maintaining estimation accuracy.
The method emphasizes the importance of adaptive mechanisms in enhancing the security of state estimation processes in nonlinear systems.

Abstract

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.

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