SYSYDSOCMar 22, 2011

Design and analysis of continuous hybrid differentiator

arXiv:1103.431128 citationsh-index: 19
Originality Synthesis-oriented
AI Analysis

For control systems requiring accurate derivative estimation, this work offers an incremental improvement over existing sliding mode differentiators by reducing chattering and enhancing performance.

The paper introduces a continuous hybrid differentiator that reduces chattering and improves dynamical performance by combining linear and nonlinear terms with sliding mode and linear filtering, achieving strong robustness.

In this paper, a continuous hybrid differentiator is presented based on a strong Lyapunov function. The differentiator design can not only reduce sufficiently chattering phenomenon of derivative estimation by introducing a perturbation parameter, but also the dynamical performances are improved by adding linear correction terms to the nonlinear ones. Moreover, strong robustness ability is obtained by integrating sliding mode items and the linear filter. Frequency analysis is applied to compare the hybrid continuous differentiator with sliding mode differentiator. The merits of the continuous hybrid differentiator include the excellent dynamical performances, restraining noises sufficiently, and avoiding the chattering phenomenon.

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