Abstract
We discuss an interpolatory model reduction framework for quadratic-bilinear (QB) descriptor systems, arising especially from the semi-discretization of the Navier–Stokes equations. Several recent results indicate that directly applying interpolatory model reduction frameworks, developed for systems of ordinary differential equations, to descriptor systems, may lead to an unbounded error between the original and reduced-order systems, e.g., in the \(\mathscr {H}_2\)-norm, due to an inappropriate treatment of the polynomial part of the original system. Thus, the main goal of this article is to extend the recently studied interpolation-based optimal model reduction framework for QB ordinary differential equations (QBODEs) to aforementioned descriptor systems while ensuring bounded error. For this, we first aim at transforming the descriptor system into an equivalent ODE system by means of projectors for which standard model reduction techniques can be applied. Subsequently, we discuss how to construct optimal reduced systems corresponding to an equivalent ODE, without requiring explicit computation of the expensive projection used in the analysis. The efficiency of the proposed algorithm is illustrated by means of a numerical example, obtained via semi-discretization of the Navier–Stokes equations.
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References
Ahmad, M.I., Benner, P., Goyal, P., Heiland, J.: Moment-matching based model reduction for Navier-Stokes type quadratic-bilinear descriptor systems. Z. Angew. Math. Mech (2017)
Antoulas, A.C.: Approximation of Large-Scale Dynamical Systems. SIAM Publications, Philadelphia, PA (2005)
Astrid, P., Weiland, S., Willcox, K., Backx, T.: Missing point estimation in models described by proper orthogonal decomposition. IEEE Trans. Autom. Control 53(10), 2237–2251 (2008)
Baur, U., Benner, P., Feng, L.: Model order reduction for linear and nonlinear systems: a system-theoretic perspective. Arch. Comput. Methods Eng. 21(4), 331–358 (2014)
Behr, M., Benner, P., Heiland, J.: Example setups of Navier-Stokes equations with control and observation: Spatial discretization and representation via linear-quadratic matrix coefficients (2017). arXiv:1707.08711
Benner, P., Breiten, T.: Interpolation-based \(\cal{H}_2\)-model reduction of bilinear control systems. SIAM J. Matrix Anal. Appl. 33(3), 859–885 (2012)
Benner, P., Breiten, T.: Krylov-subspace based model reduction of nonlinear circuit models using bilinear and quadratic-linear approximations. In: Günther, M., Bartel, A., Brunk, M., Schöps, S., Striebel, M. (eds.) Progress in Industrial Mathematics at ECMI 2010. Mathematics in Industry, vol. 17, pp. 153–159. Springer-Verlag, Berlin (2012)
Benner, P., Breiten, T.: Two-sided moment matching methods for nonlinear model reduction. Preprint MPIMD/12-12, MPI Magdeburg (2012). http://www.mpi-magdeburg.mpg.de/preprints/
Benner, P., Breiten, T.: Two-sided projection methods for nonlinear model reduction. SIAM J. Sci. Comput. 37(2), B239–B260 (2015)
Benner, P., Damm, T.: Lyapunov equations, energy functionals, and model order reduction of bilinear and stochastic systems. SIAM J. Control Optim. 49(2), 686–711 (2011)
Benner, P., Goyal, P.: Multipoint interpolation of Volterra series and \(\cal{H}_2\)-model reduction for a family of bilinear descriptor systems. Syst. Control Lett. 97, 1–11 (2016)
Benner, P., Goyal, P.: Balanced truncation model order reduction for quadratic-bilinear control systems (2017). arXiv:1705.00160
Benner, P., Goyal, P., Gugercin, S.: \(\cal{H}_2 \)-quasi-optimal model order reduction for quadratic-bilinear control systems (2016). arXiv:1610.03279
Benner, P., Mehrmann, V., Sorensen, D.C.: Dimension Reduction of Large-Scale Systems, vol. 45. Lecture Notes in Computational Science and Engineering. Springer, Heidelberg (2005)
Chaturantabut, S., Sorensen, D.C.: Nonlinear model reduction via discrete empirical interpolation. SIAM J. Sci. Comput. 32(5), 2737–2764 (2010)
Flagg, G., Gugercin, S.: Multipoint Volterra series interpolation and \(\cal{H}_2\) optimal model reduction of bilinear systems. SIAM J. Matrix Anal. Appl. 36(2), 549–579 (2015)
Goyal, P., Benner, P.: An iterative model order reduction scheme for a special class of bilinear descriptor systems appearing in constraint circuit simulation. In: ECCOMAS Congress 2016, VII European Congress on Computational Methods in Applied Sciences and Engineering, vol. 2, pp. 4196–4212 (2016)
Gu, C.: QLMOR: a projection-based nonlinear model order reduction approach using quadratic-linear representation of nonlinear systems. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 30(9), 1307–1320 (2011)
Gugercin, S., Stykel, T., Wyatt, S.: Model reduction of descriptor systems by interpolatory projection methods. SIAM J. Sci. Comput. 35(5), B1010–B1033 (2013)
Hairer, E., Wanner, G.: Solving Ordinary Differential Equations II-Stiff and Differential-Algebraic Problems, 2nd edn. Springer Series in Computational Mathematics. Springer (2002)
Heinkenschloss, M., Sorensen, D.C., Sun, K.: Balanced truncation model reduction for a class of descriptor systems with applications to the Oseen equations. SIAM J. Sci. Comput. 30(2), 1038–1063 (2008)
Hinze, M., Volkwein, S.: Proper orthogonal decomposition surrogate models for nonlinear dynamical systems: error estimates and suboptimal control. In: [14], pp. 261–306
Kolda, T.G., Bader, B.W.: Tensor decompositions and applications. SIAM Rev. 51(3), 455–500 (2009)
Kunisch, K., Volkwein, S.: Galerkin proper orthogonal decomposition methods for a general equation in fluid dynamics. SIAM J. Numer. Anal. 40(2), 492–515 (2002)
Kunisch, K., Volkwein, S.: Proper orthogonal decomposition for optimality systems. ESAIM Math. Model. Numer. Anal. 42(1), 1–23 (2008)
Schilders, W.H.A., van der Vorst, H.A., Rommes, J.: Model Order Reduction: Theory, Research Aspects and Applications. Springer, Heidelberg (2008)
Zhang, L., Lam, J.: On \(H_2\) model reduction of bilinear systems. Automatica 38(2), 205–216 (2002)
Acknowledgements
The authors would like to thank Dr. Jan Heiland for providing the lid-driven cavity model, used in the numerical experiment.
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Benner, P., Goyal, P. (2018). An Iterative Model Reduction Scheme for Quadratic-Bilinear Descriptor Systems with an Application to Navier–Stokes Equations. In: Keiper, W., Milde, A., Volkwein, S. (eds) Reduced-Order Modeling (ROM) for Simulation and Optimization. Springer, Cham. https://doi.org/10.1007/978-3-319-75319-5_1
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