Skip to main content

An Iterative Model Reduction Scheme for Quadratic-Bilinear Descriptor Systems with an Application to Navier–Stokes Equations

  • Chapter
  • First Online:
Reduced-Order Modeling (ROM) for Simulation and Optimization

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 49.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 64.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 99.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. 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)

    Google Scholar 

  2. Antoulas, A.C.: Approximation of Large-Scale Dynamical Systems. SIAM Publications, Philadelphia, PA (2005)

    Book  Google Scholar 

  3. 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)

    Article  MathSciNet  Google Scholar 

  4. 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)

    Article  MathSciNet  Google Scholar 

  5. 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

  6. 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)

    Article  MathSciNet  Google Scholar 

  7. 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)

    Chapter  Google Scholar 

  8. 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/

  9. Benner, P., Breiten, T.: Two-sided projection methods for nonlinear model reduction. SIAM J. Sci. Comput. 37(2), B239–B260 (2015)

    Article  MathSciNet  Google Scholar 

  10. 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)

    Article  MathSciNet  Google Scholar 

  11. 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)

    Article  Google Scholar 

  12. Benner, P., Goyal, P.: Balanced truncation model order reduction for quadratic-bilinear control systems (2017). arXiv:1705.00160

  13. Benner, P., Goyal, P., Gugercin, S.: \(\cal{H}_2 \)-quasi-optimal model order reduction for quadratic-bilinear control systems (2016). arXiv:1610.03279

  14. 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)

    Google Scholar 

  15. Chaturantabut, S., Sorensen, D.C.: Nonlinear model reduction via discrete empirical interpolation. SIAM J. Sci. Comput. 32(5), 2737–2764 (2010)

    Article  MathSciNet  Google Scholar 

  16. 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)

    Article  MathSciNet  Google Scholar 

  17. 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)

    Google Scholar 

  18. 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)

    Article  Google Scholar 

  19. Gugercin, S., Stykel, T., Wyatt, S.: Model reduction of descriptor systems by interpolatory projection methods. SIAM J. Sci. Comput. 35(5), B1010–B1033 (2013)

    Article  MathSciNet  Google Scholar 

  20. Hairer, E., Wanner, G.: Solving Ordinary Differential Equations II-Stiff and Differential-Algebraic Problems, 2nd edn. Springer Series in Computational Mathematics. Springer (2002)

    Google Scholar 

  21. 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)

    Article  MathSciNet  Google Scholar 

  22. Hinze, M., Volkwein, S.: Proper orthogonal decomposition surrogate models for nonlinear dynamical systems: error estimates and suboptimal control. In: [14], pp. 261–306

    Google Scholar 

  23. Kolda, T.G., Bader, B.W.: Tensor decompositions and applications. SIAM Rev. 51(3), 455–500 (2009)

    Article  MathSciNet  Google Scholar 

  24. 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)

    Article  MathSciNet  Google Scholar 

  25. Kunisch, K., Volkwein, S.: Proper orthogonal decomposition for optimality systems. ESAIM Math. Model. Numer. Anal. 42(1), 1–23 (2008)

    Article  MathSciNet  Google Scholar 

  26. Schilders, W.H.A., van der Vorst, H.A., Rommes, J.: Model Order Reduction: Theory, Research Aspects and Applications. Springer, Heidelberg (2008)

    Book  Google Scholar 

  27. Zhang, L., Lam, J.: On \(H_2\) model reduction of bilinear systems. Automatica 38(2), 205–216 (2002)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Dr. Jan Heiland for providing the lid-driven cavity model, used in the numerical experiment.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pawan Goyal .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

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

Download citation

Publish with us

Policies and ethics