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A global robust iterative learning position control for current-fed permanent magnet step motors
We address the tracking control problem via state feedback for uncertain current-fed permanent magnet step motors with non-sinusoidal flux distribution: a periodic reference signal (of known period) for the rotor position is required to be tracked. We design a robust iterative learning control algor...
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Main Authors: | , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | We address the tracking control problem via state feedback for uncertain current-fed permanent magnet step motors with non-sinusoidal flux distribution: a periodic reference signal (of known period) for the rotor position is required to be tracked. We design a robust iterative learning control algorithm which, for any motor initial condition and without requiring any resetting procedure, guarantees, despite system uncertainties: exponential convergence of the rotor position tracking error to a residual ball (centered at the origin) whose radius can be made arbitrarily small by properly setting the learning gain; asymptotic convergence of the rotor position tracking error to zero. Robustness with respect to a finite memory implementation of the control algorithm based on the piecewise linear approximation theory is shown to be guaranteed. |
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ISSN: | 2163-5137 |
DOI: | 10.1109/ISIE.2010.5637626 |