Adaptive feedforward controller for a DC motor drive based on inverse dynamic model with recursive least squares parameter estimation

摘要

This article deals with the development of a simple adaptive controller for DC motor drives, based on the feed forward compensation of the drive's dynamic. Several variants of the drive's inverse model are proposed in both continuous and discrete form. The model's parameters are estimated online using the Recursive Least Squares method. A polynomial approximation filter (Savitzky-Golay) to determine noisy measured signal derivatives is used to estimate all of the inverse dynamic model's states. The resulting control algorithm is able to learn a complete model of the dynamics without any need for adjusting or setting user parameters. The paper also covers real experiments conducted to test the behaviour of the developed algorithm.