Articles | Volume 16
https://doi.org/10.5194/ars-16-89-2018
https://doi.org/10.5194/ars-16-89-2018
04 Sep 2018
 | 04 Sep 2018

Order reduction of hierarchical interconnected dynamical systems

Michael Popp and Wolfgang Mathis

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Cited articles

Antoulas, A. C.: Approximation of Large-Scale Dynamical Systems, Siam, Philadelphia, PA, 2005.
Antoulas, A. C., Sorensen, D. C., and Gugercin, S.: A survey of model reduction methods for large-scale systems, Contemp. Math., 280, 193–219, 2001.
Baur, U., Benner, P., and Feng, L.: Model Order Reduction for Linear and Nonlinear Systems: A System-Theoretic Perspective, Arch. Comput. Method. E., 21, 331–358, 2014.
Chen, Y. and White, J. K.: A Quadratic Method for Nonlinear Model Order Reduction, in: Technical Proceedings of the International Conference on Modeling and Simulation of Microsystems, Massachusetts Institute of Technology, US, 477–480, 2000.
Condon, M. and Rossen, I.: Empirical balanced truncation of nonlinear systems, J. Nonlinear. Sci., 14, 504–414, 2004.
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Short summary
The simulation of large scale nonlinear dynamical interconnected systems is a usual task. Due to the high complexity of the considered systems, the principle of thinking in hierarchical structures is common among engineers. This contribution proposes an approach for the numerical simulation of large systems, which keeps the hierarchical system structure alive during the entire simulation and order reduction process, which results in several benefits compared with the state of the art.