Secure state estimation for affine T-S fuzzy systems under sparse sensor attacks

Abstract

This paper is concerned with the secure state estimation problem of affine T-S fuzzy systems under sparse sensor attacks. The objective is to construct a bank of fuzzy state estimators with an adaptive switching mechanism to ensure the attacked sensor measurements be isolated, and the estimation error system is asymptotic stable with a guaranteed H∞ performance. The case of unmeasurable plant premise variables is considered, which leads to the estimator implementation according to estimators’ state-space partitions may not be always synchronous with the plant. By constructing piecewise Lyapunov functions and employing the S-procedure and matrices decoupled techniques, the constructed state estimators synthesis conditions are derived in linear matrix inequalities (LMIs) form. Compared with existing methods, the proposed approach avoids restrictions on the structure of Lyapunov matrices and derives less conservative estimator design conditions. Finally, the effectiveness and superiorities of the proposed method is verified with a numerical example.