Paper
30 March 2010 Proper orthogonal decomposition with updates for efficient control design in smart material systems
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Abstract
Proper orthogonal decomposition (POD) is a basis reduction technique that allows simulations of complicated systems to be calculated at faster speeds with minimal loss of accuracy. The reduced order basis is created from a set of system data called snapshots. The speed and information retention of POD make it an attractive method to implement reduced-order models of smart material systems. This can allow for the modeling of larger systems and the implementation of real time control, which may be impossible when using the full-order system. There are times when the dynamics of a system can change during a simulation, and the addition of more information to the set of snapshots would be beneficial. The implementation of control on a system is a time when adding new snapshots to the collection can increase the accuracy of the model. Using updates allows more flexibility when trying to balance the accuracy and the speed of the simulation. By updating the POD basis at specific times throughout the interval, we can increase the accuracy of the model and control by using a greater amount of the information given by the snapshots, while we can increase the speed of the simulation during times when using less information will still result in sufficient accuracy.
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Stephen F. May and Ralph C. Smith "Proper orthogonal decomposition with updates for efficient control design in smart material systems", Proc. SPIE 7644, Behavior and Mechanics of Multifunctional Materials and Composites 2010, 764407 (30 March 2010); https://doi.org/10.1117/12.847579
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KEYWORDS
Chemical elements

Control systems

Neptunium

Computer simulations

Matrices

Smart materials

Systems modeling

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