This paper proposes a new model-free sliding mode tracking differentiator with adaptive gains for reliable filtering and derivative estimations from noisy signals by improving a Levant and Yu's sliding mode tracking differentiator. Particularly, the proposed tracking differentiator employs a nested generalized signum function for reducing overshoot during convergence. Moreover, a model-free adaptive gain scheduling is adopted for balancing the tracking and filtering performances. The advantages of the proposed tracking differentiator is validated through numerical examples.

中文翻译：

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具有自适应增益的滑模跟踪微分器，用于噪声信号的滤波和导数估计


本文提出了一种新的无模型滑模跟踪微分器，通过改进 Levant 和 Yu 的滑模跟踪微分器，该微分器具有自适应增益，可以对噪声信号进行可靠的滤波和导数估计。特别地，所提出的跟踪微分器采用嵌套广义正负号函数来减少收敛期间的超调。此外，采用无模型自适应增益调度来平衡跟踪和滤波性能。通过数值例子验证了所提出的跟踪微分器的优点。