1997
DOI: 10.1006/jsvi.1996.1030
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Constrained Quadratic Programming, Active Control of Rotating Mass Imbalance

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Cited by 14 publications
(10 citation statements)
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“…Previously, a number of unbalance control schemes have been proposed for magnetic bearings in which the controller acts on measurements of rotor displacements and produces synchronous control forces at the bearings, updated in an iterative manner to cancel the effects of unbalance forces e.g. [9][10][11][12][13]. Although situations involving rotor-stator contact are not considered in these studies, a similar control approach will be used here.…”
Section: Control Implicationsmentioning
confidence: 99%
“…Previously, a number of unbalance control schemes have been proposed for magnetic bearings in which the controller acts on measurements of rotor displacements and produces synchronous control forces at the bearings, updated in an iterative manner to cancel the effects of unbalance forces e.g. [9][10][11][12][13]. Although situations involving rotor-stator contact are not considered in these studies, a similar control approach will be used here.…”
Section: Control Implicationsmentioning
confidence: 99%
“…The H -in nity design (6) overcomes this problem, but at the expense of steady state performance. Again, the steady state norm-bound controller design (7) achieves the best combination of robust stability and performance.…”
Section: Predicted Controller Performancementioning
confidence: 99%
“…Such methods have been enhanced with improved robustness features and techniques to address speed dependence or control multiple disturbance frequencies [4,5]. F urther studies have considered controller designs for optimized transient vibration control [6][7][8], e.g. during rotor mass losstype events.…”
mentioning
confidence: 99%
“…The ideal control system design assumes that any magnitude of control is feasible. Within all systems, however, a limit must exist on the available control energy [7]. Saturation causes there to be a difference between the expected and actual control signals which leads to a resulting difference between the expected and actual system outputs.…”
Section: Introductionmentioning
confidence: 96%