SYSYSep 20, 2025

Prescribed-Time Observer Is Naturally Robust Against Disturbances and Uncertainties

arXiv:2509.168361.2h-index: 1
Originality Incremental advance
AI Analysis

For control systems engineers, this provides a robust observer design that guarantees estimation despite significant disturbances, though the method is an extension of existing prescribed-time approaches.

The paper proves that a prescribed-time observer for nonlinear systems can completely reject arbitrarily large bounded disturbances and unmodeled dynamics, achieving accurate state and disturbance estimation, and outperforms high-gain observers by reducing peaking and improving accuracy.

This paper addresses the robustness of a prescribed-time observer for a class of nonlinear systems in the presence of disturbances and unmodeled dynamics. It is proven and demonstrated through simulations that the proposed observer completely rejects the effects of arbitrarily large bounded disturbances and unmodeled dynamics, enabling accurate estimation of both the states and the disturbances. Furthermore, a comparison with the standard high-gain observer is provided to highlight the superiority of the prescribed-time observer in reducing the peaking phenomenon and improving estimation accuracy.

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