Sensor Attacks Detection and Reconstruction for AUVs: An Improved Zonotopic Analysis Approach
Chaojiang Liang, Zhihua Guo, Ben Niu, Ning Wang, Ying Zhao, Zhiguang Feng · IEEE Internet of Things Journal · 2025
This article studies the attack detection and reconstruction problem for autonomous underwater vehicles (AUVs) subject to unknown but bounded disturbances and measurement noise. First, a Takagi-Sugeno (T-S) fuzzy model is utilized to address the nonlinearity of AUVs. Then, a$H_{\infty }$T-N-L observer is introduced to estimate system state. Subsequently, to improve the accuracy of attack detection, an improved attack detection method within the T-S fuzzy system framework is obtained by the reachability analysis of the residual. Afterwards, the effect of disturbances and measurement noise on attack reconstruction and isolation is analyzed. The accuracy of attack reconstruction and isolation for T-S fuzzy systems is improved by zonotopic analysis. Finally, the effectiveness and advantages of the proposed method are verified through simulation results.