Abstract
In this paper we review the status of existing techniques for nonlinear model order reduction by investigating how well these techniques perform for typical industrial needs. In particular the Trajectory Piecewise Linear-method and the Proper Orthogonal Decomposion approach are taken under consideration.
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Notes
- 1.
Most frequently \(\mathbf{V}\) is constructed to be orthogonal, such that \(\mathbf{W}=\mathbf{V}\) can be chosen.
- 2.
Similar results are obtained from a matlab-implementation using ode15s as integration scheme.
- 3.
The models used arise from linearization around the states the system was in during training at \(t\in \{0.0, 3.01943, 3.04244\}\).
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Acknowledgements
The work presented is funded by the Marie-Curie Transfer-of-Knowledge project O-MOORE-NICE! under call Identifier FP6-2005-Mobility-3.
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Striebel, M., Rommes, J. (2011). Model Order Reduction of Nonlinear Systems in Circuit Simulation: Status and Applications. In: Benner, P., Hinze, M., ter Maten, E. (eds) Model Reduction for Circuit Simulation. Lecture Notes in Electrical Engineering, vol 74. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0089-5_17
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