Kybernetika 62 no. 3, 513-526, 2026

Observer design for a class of nonlinear descriptor systems with measurement noise

Yanjun Shen, Haonan Su, Chenhao Zhao and Fei LongDOI: 10.14736/kyb-2026-3-0513

Abstract:

In this paper, a robust $H_{\infty}$ observer design method is proposed for a class of nonlinear descriptor systems subject to measurement noise and unknown disturbances. Specifically, a novel augmented system is constructed based on the output filtering method. Next, an observer resisting measurement noise is presented and the state estimation error system is derived. The observer parameters are parameterized by employing the generalized inverse technique for matrices. Finally, sufficient conditions ensuring the asymptotic stability of the state estimation error system with the $H_{\infty}$ performance index are derived on the basis of the linear matrix inequalities~(LMIs). Compared to the conventional robust $H_{\infty}$ observers, simulation results demonstrate that the proposed method alleviates the adverse effects of measurement noise on the state estimation and results in smaller estimation errors.

Keywords:

descriptor systems, $H_{\infty }$ observer, linear matrix inequalities (LMIs), output filtering method

Classification:

93B36, 93C10

paper.pdf

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