Adaptive Tracking of a Multi-Sinusoidal Signal with DREM-Based Parameters Estimation

摘要

In this paper tracking of an unknown multi-sinusoidal signal with fast online frequency estimation is addressed. The latter has been achieved by the so-called dynamic regressor extension and mixing (DREM) approach, which allows to increase performance of multiple frequency estimation. Designed predictive compensation algorithm is capable to operate under presence of computational or transmission delays. The resultant controller has been implemented to a robotic arm with a computer vision system. An extensive experimental study shows undoubted advantages of the DREM-based frequency estimator in comparison to the classical gradient approach. A detailed analysis of the transient response properties is provided in the paper.