Sliding Mode Tracking Differentiator With Adaptive Gains for Filtering and Derivative Estimation of Noisy Signals

Abstract

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.

Keywords

• Sliding mode tracking differentiator
• adaptive gain
• filtering
• derivative estimation
• overshoot reduction