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

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 estim...

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Bibliographic Details
Published in:	2016 17th International Conference on Mechatronics - Mechatronika (ME) pp. 1 - 5
Main Authors:	Brablc, Martin, Sova, Vaclav, Grepl, Robert
Format:	Conference Proceeding
Language:	English
Published:	Czech Technical University in Prague 01.12.2016
Subjects:	adaptive control DC motor drive DC motors feedforward compensation Feedforward neural networks Finite impulse response filters Heuristic algorithms Low-pass filters Mathematical model online parameter estimation Rapid control prototyping Recursive least squares Savitzky-Golay filter Torque
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Summary:	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.