Abstract
In this paper, a linear parameter-varying (LPV) control design method is
evaluated experimentally on an active magnetic bearing (AMB) system. A
speed-dependent LPV model of the AMB system is derived. Model
uncertainties are identified using artificial neural networks, and an
uncertainty weighting function is approximated for LPV control
synthesis. Experiments are conducted to verify the robustness of LPV
controllers for a wide range of rotational speed. This LPV control
approach eliminates the need for gain-scheduling, and provides better
performance than the traditional proportional-integral-derivative
control for high-speed operation.
Original language | English |
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Pages (from-to) | 1161 - 1172 |
Number of pages | 12 |
Journal | Control Engineering Practice |
Volume | 16 |
DOIs | |
Publication status | Published - 2008 |
MoE publication type | A1 Journal article-refereed |