A novel sliding mode based nonlinear tracking differentiator for filtering noise

Obtaining reliable signals and their derivatives is important from noisy input signals. Toward this problem, this paper presents a novel nonlinear tracking differentiator (TD-N) based on sliding mode for filtering the noise of input signals and estimating their derivatives. TD-N is an improvement of Denis et al.’s nonlinear tracking differentiator by adopting a sigmoid function and a power function to balance the trade-off between filtering performance and responding speed. The validity of TD-N is evaluated through Numerical simulation examples.