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Nonlinear model order reduction using remainder functions

Published: 06 March 2006 Publication History

Abstract

This paper describes a novel approach to the problem of model order reduction (MOR) of very large nonlinear systems. We consider the behavior of a dynamic nonlinear system as having two fundamental characteristics: a global behavioral "envelope" that describes major transformations to the state of the system under external stimuli and a local behavior that describes small perturbation responses. The nonlinear low order envelope function is generated by using the remainders from the coalescence of projection bases taken through a space-state sample. A behavioral model can then be expressed as the superposition of these two descriptions, operating according to the input stimuli and the current state value.

References

[1]
M. Rewienski and J. White, "A Trajectory Piecewise-Linear Approach to Model Order Reduction and Fast Simulation of Nonlinear Circuits and Micromachined Devices," IEEE Trans. CAD, 22(2), Feb. 2003.
[2]
N. Dong and J. Roychowdhoury, "Piecewise Polynomial Nonlinear Model Order Reduction," Proc. of 40th IEEE/ACM Design Automation Conference, DAC 2003, pp. 484 489, 2003.
[3]
L. Ljung in System Identification: Theory for the User, Prentice-Hall, Inc., 1987.

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Published In

cover image Guide Proceedings
DATE '06: Proceedings of the conference on Design, automation and test in Europe: Proceedings
March 2006
1390 pages
ISBN:3981080106

Sponsors

  • EDAA: European Design Automation Association
  • The EDA Consortium
  • IEEE-CS\DATC: The IEEE Computer Society

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European Design and Automation Association

Leuven, Belgium

Publication History

Published: 06 March 2006

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DATE '06 Paper Acceptance Rate 267 of 834 submissions, 32%;
Overall Acceptance Rate 518 of 1,794 submissions, 29%

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