Rapid-convergent nonlinear differentiator
For control systems requiring fast and accurate derivative estimation, this work offers an incremental improvement over existing differentiators by reducing chattering and enhancing robustness.
The paper presents a nonlinear differentiator that achieves rapid convergence by combining a continuous power function with linear correction terms, reducing chattering and improving dynamic performance. Simulations and experiments confirm its effectiveness.
A nonlinear differentiator being fit for rapid convergence is presented, which is based on singular perturbation technique. The differentiator design can not only sufficiently reduce the chattering phenomenon of derivative estimation by introducing a continuous power function, but the dynamical performances are also improved by adding linear correction terms to the nonlinear ones. Moreover, strong robustness ability is obtained by integrating nonlinear items and the linear filter. The merits of the rapid-convergent differentiator include the excellent dynamical performances, restraining noises sufficiently, avoiding the chattering phenomenon and being not based on system model. The theoretical results are confirmed by computer simulations and an experiment.