Acceso abierto

Stabilized model reduction for nonlinear dynamical systems through a contractivity-preserving framework


Cite

Aminzare, Z. and Sontag, E.D. (2013). Logarithmic Lipschitz norms and diffusion-induced instability, Nonlinear Analysis: Theory, Methods & Applications83: 31–49.10.1016/j.na.2013.01.001366619123729972Search in Google Scholar

Aminzare, Z. and Sontag, E.D. (2014). Contraction methods for nonlinear systems: A brief introduction and ome open problems, 53rd IEEE Conference on Decision and Control, Los Angeles, CA, USA, pp. 3835–3847.Search in Google Scholar

Astrid, P. (2004). Reduction of Process Simulation Models: A Proper Orthogonal Decomposition Approach, PhD thesis, University of Technology, Eindhoven.Search in Google Scholar

Astrid, P., Weiland, S., Willcox, K. and Backx, T. (2008). Missing point estimation in models described by proper orthogonal decomposition, IEEE Transactions on Automatic Control53(10): 2237–2251.10.1109/TAC.2008.2006102Search in Google Scholar

Banasiak, J. (2020). Logarithmic norms and regular perturbations of differential equations, Annales Universitatis Mariae Curie-Sklodowska, Sectio A: Mathematica73(2): 5–19.10.17951/a.2019.73.2.5-19Search in Google Scholar

Barrault, M., Maday, Y., Nguyen, N.C. and Patera, A.T. (2004). An ‘empirical interpolation’ method: Application to efficient reduced-basis discretization of partial differential equations, Comptes Rendus Mathematique339(9): 667–672.10.1016/j.crma.2004.08.006Search in Google Scholar

Bartoszewicz, A. and Adamiak, K. (2019). A reference trajectory based discrete time sliding mode control strategy, International Journal of Applied Mathematics and Computer Science29(3): 517–525, DOI: 10.2478/amcs-2019-0038.10.2478/amcs-2019-0038Search in Google Scholar

Benda, M. (1998). A central limit theorem for contractive stochastic dynamical systems, Journal of Applied Probability35(1): 200–205.10.1239/jap/1032192562Search in Google Scholar

Berkooz, G., Holmes, P. and Lumley, J.L. (1993). The proper orthogonal decomposition in the analysis of turbulent flows, Annual Review of Fluid Mechanics25(1): 539–575.10.1146/annurev.fl.25.010193.002543Search in Google Scholar

Blocher, C., Saveriano, M. and Lee, D. (2017). Learning stable dynamical systems using contraction theory, 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Jeju, South Korea, pp. 124–129.Search in Google Scholar

Carlberg, K., Tuminaro, R. and Boggs, P. (2015). Preserving Lagrangian structure in nonlinear model reduction with application to structural dynamics, SIAM Journal on Scientific Computing37(2): B153–B184, DOI: 10.1137/140959602.10.1137/140959602Search in Google Scholar

Chaturantabut, S. (2017). Temporal localized nonlinear model reduction with a priori error estimate, Applied Numerical Mathematics119: 225–238.10.1016/j.apnum.2017.02.014Search in Google Scholar

Chaturantabut, S., Beattie, C. and Gugercin, S. (2016). Structure-preserving model reduction for nonlinear port-Hamiltonian systems, SIAM Journal on Scientific Computing38(5): B837–B865, DOI: 10.1137/15M1055085.10.1137/15M1055085Search in Google Scholar

Chaturantabut, S. and Sorensen, D. (2012). A state space error estimate for POD-DEIM nonlinear model reduction, SIAM Journal on Numerical Analysis50(1): 46–63, DOI: 10.1137/110822724.10.1137/110822724Search in Google Scholar

Chaturantabut, S. and Sorensen, D.C. (2010). Nonlinear model reduction via discrete empirical interpolation, SIAM Journal on Scientific Computing32(5): 2737–2764, DOI: 10.1137/090766498.10.1137/090766498Search in Google Scholar

Chaturantabut, S. and Sorensen, D.C. (2011). Application of POD and DEIM on dimension reduction of non-linear miscible viscous fingering in porous media, Mathematical and Computer Modelling of Dynamical Systems17(4): 337–353.10.1080/13873954.2011.547660Search in Google Scholar

Dahlquist, G. (1959). Stability and error bounds in the numerical integration of ordinary differential equations, Transactions of the Royal Institute of Technology (130).Search in Google Scholar

Feng, Z. and Soulaimani, A. (2007). Reduced order modelling based on pod method for 3D nonlinear aeroelasticity, 18th IASTED International Conference on Modelling and Simulation, MS’07, Montreal, Quebec, Canada, pp. 489–494.Search in Google Scholar

Ghasemi, M., Yang, Y., Gildin, E., Efendiev, Y. and Calo, V. (2015). Fast multiscale reservoir simulations using POD-DEIM model reduction, SPE Reservoir Simulation Symposium, Houston, TX, USA.10.2118/173271-MSSearch in Google Scholar

Ghavamian, F., Tiso, P. and Simone, A. (2017). POD-DEIM model order reduction for strain-softening viscoplasticity, Computer Methods in Applied Mechanics and Engineering317: 458–479.10.1016/j.cma.2016.11.025Search in Google Scholar

Gurka, R., Liberzon, A. and Hetsroni, G. (2006). POD of vorticity fields: A method for spatial characterization of coherent structures, International Journal of Heat and Fluid Flow27(3): 416–423.10.1016/j.ijheatfluidflow.2006.01.001Search in Google Scholar

Habibi, J., Moshiri, B. and Sedigh, A.K. (2008). Contractive predictive control of mixed logical dynamical hybrid systems, International Journal of Innovative Computing, Information and Control4(6): 1283–1298.Search in Google Scholar

Hairer, E., Nørsett, S.P. and Wanner, G. (1993). Solving Ordinary Differential Equations I: Nonstiff Problems, 2nd Edn, Springer, Berlin.Search in Google Scholar

Hinze, M., Kunkel, M., Steinbrecher, A. and Stykel, T. (2012). Model order reduction of coupled circuit-device systems, International Journal of Numerical Modelling: Electronic Networks, Devices and Fields25(4): 362–377, DOI: 10.1002/jnm.840.10.1002/jnm.840Search in Google Scholar

Hochman, A., Bond, B. and White, J. (2011). A stabilized discrete empirical interpolation method for model reduction of electrical, thermal, and microelectromechanical systems, 48th ACM/EDAC/IEEE Design Automation Conference (DAC), New York, NY, USA, pp. 540–545.Search in Google Scholar

Intawichai, S. and Chaturantabut, S. (2020). A numerical study of efficient sampling strategies for randomized singular value decomposition, Thai Journal of Mathematics: 371–385.Search in Google Scholar

Isoz, M. (2019). POD-DEIM based model order reduction for speed-up of flow parametric studies, Ocean Engineering186: 106083.10.1016/j.oceaneng.2019.05.065Search in Google Scholar

Jouffroy, J. (2005). Some ancestors of contraction analysis, Proceedings of the 44th IEEE Conference on Decision and Control, Seville, Spain, pp. 5450–5455.Search in Google Scholar

Kellems, A.R., Chaturantabut, S., Sorensen, D.C. and Cox, S.J. (2010). Morphologically accurate reduced order modeling of spiking neurons, Journal of Computational Neuroscience28(3): 477–494, DOI: 10.1007/s10827-010-0229-4.10.1007/s10827-010-0229-420300957Search in Google Scholar

Kunisch, K. and Volkwein, S. (2010). Optimal snapshot location for computing POD basis functions, ESAIM: Mathematical Modelling and Numerical Analysis44(3): 509–529.10.1051/m2an/2010011Search in Google Scholar

Lanata, F. and Grosso, A. D. (2006). Damage detection and localization for continuous static monitoring of structures using a proper orthogonal decomposition of signals, Smart Materials and Structures15(6): 1811–1829.10.1088/0964-1726/15/6/036Search in Google Scholar

Lohmiller, W. and Slotine, J.J.E. (1998). On contraction analysis for non-linear systems, Automatica34(6): 683–696.10.1016/S0005-1098(98)00019-3Search in Google Scholar

Lohmiller, W. and Slotine, J.J.E. (2000a). Control system design for mechanical systems using contraction theory, IEEE Transactions on Automatic Control45(5): 984–989.10.1109/9.855568Search in Google Scholar

Lohmiller, W. and Slotine, J.J.E. (2000b). Nonlinear process control using contraction theory, AIChE Journal46(3): 588–596.10.1002/aic.690460317Search in Google Scholar

Lozinskii, S.M. (1958). Error estimates for the numerical integration of ordinary differential equations. Part I, Izvestiya Vysshikh Uchebnykh Zavedenii: Matematika6(5): 52–90, (in Russian).Search in Google Scholar

Peigné, M. and Woess, W. (2011). Stochastic dynamical systems with weak contractivity properties. II: Iteration of Lipschitz mappings, Colloquium Mathematicum125(1): 55–81.Search in Google Scholar

Pham, Q.-C., Tabareau, N. and Slotine, J.-J. (2009). A contraction theory approach to stochastic incremental stability, IEEE Transactions on Automatic Control54(4): 816–820.10.1109/TAC.2008.2009619Search in Google Scholar

Rewieński, M.J. (2003). A Trajectory Piecewise-Linear Approach to Model Order Reduction of Nonlinear Dynamical Systems, PhD thesis, Massachusetts Institute of Technology, Cambridge, MA.Search in Google Scholar

Rewienski, M. and White, J. (2001). A trajectory piecewise-linear approach to model order reduction and fast simulation of nonlinear circuits and micromachined devices, International Conference on Computer-Aided Design, San Jose, CA, USA, p. 252.Search in Google Scholar

Rewienski, M. and White, J. (2003). A trajectory piecewise-linear approach to model order reduction and fast simulation of nonlinear circuits and micromachined devices, IEEE Transactions Computer-Aided Design of Integrated Circuits and Systems22(2): 155–170.10.1109/TCAD.2002.806601Search in Google Scholar

Rewienski, M. and White, J. (2006). Model order reduction for nonlinear dynamical systems based on trajectory piecewise-linear approximations, Linear Algebra and Its Applications415(2–3): 426–454.10.1016/j.laa.2003.11.034Search in Google Scholar

Russo, G. and di Bernardo, M. (2011). On contraction of piecewise smooth dynamical systems, IFAC Proceedings Volumes44(1): 13299–13304.10.3182/20110828-6-IT-1002.02810Search in Google Scholar

Sanjuan, A., Rotondo, D., Nejjari, F. and Sarrate, R. (2019). An LMI-based heuristic algorithm for vertex reduction in LPV systems, International Journal of Applied Mathematics and Computer Science29(4): 725–737, DOI: 10.2478/amcs-2019-0054.10.2478/amcs-2019-0054Search in Google Scholar

Schenone, E. (2014). Reduced Order Models, Forward and Inverse Problems in Cardiac Electrophysiology, Thesis, Université Pierre et Marie Curie Paris VI, Paris, https://tel.archives-ouvertes.fr/tel-01092945.Search in Google Scholar

Simpson-Porco, J.W. and Bullo, F. (2014). Contraction theory on Riemannian manifolds, Systems & Control Letters65: 74–80.10.1016/j.sysconle.2013.12.016Search in Google Scholar

Söderlind, G. (1986). Bounds on nonlinear operators in finite-dimensional Banach spaces, Numerische Mathematik50(1): 27–44, DOI: 10.1007/BF01389666.10.1007/BF01389666Search in Google Scholar

Söderlind, G. (2006). The logarithmic norm: History and modern theory, BIT Numerical Mathematics46(3): 631–652, DOI: 10.1007/s10543-006-0069-9.10.1007/s10543-006-0069-9Search in Google Scholar

Sontag, E.D. (2010). Contractive systems with inputs, in J.C. Willems et al. (Eds), Perspectives in Mathematical System Theory, Control and Signal Processing, Springer, Berlin, pp. 217–228, DOI: 10.1007/978-3-540-93918-4_20.10.1007/978-3-540-93918-4_20Search in Google Scholar

Stanko, Z.P., Boyce, S.E. and Yeh, W.W.-G. (2016). Nonlinear model reduction of unconfined groundwater flow using POD and DEIM, Advances in Water Resources97: 130–143.10.1016/j.advwatres.2016.09.005Search in Google Scholar

Sukuntee, N. and Chaturantabut, S. (2019). Model order reduction for Sine–Gordon equation using POD and DEIM, Thai Journal of Mathematics: 222–256.Search in Google Scholar

Sukuntee, N. and Chaturantabut, S. (2020). Parametric nonlinear model reduction using k-means clustering for miscible flow simulation, Journal of Applied Mathematics2020: 1–12, Article ID 3904606.10.1155/2020/3904606Search in Google Scholar

Ştefănescu, R. and Navon, I.M. (2013). POD/DEIM nonlinear model order reduction of an ADI implicit shallow water equations model, Journal of Computational Physics237: 95–114, DOI: 10.1016/j.jcp.2012.11.035.10.1016/j.jcp.2012.11.035Search in Google Scholar

Volkwein, S. (2008). Model reduction using proper orthogonal decomposition, Lecture notes, University of Konstanz, Konstanz, http://www.math.uni-konstanz.de/numerik/personen/volkwein/teaching/POD-Vorlesung.pdf.Search in Google Scholar

Walther, A., Griewank, A. and Vogel, O. (2003). ADOL-C: Automatic differentiation using operator overloading in C++, PAMM: Proceedings in Applied Mathematics and Mechanics2(1): 41–44.10.1002/pamm.200310011Search in Google Scholar

Wang, D. and Xiao, A. (2015). Dissipativity and contractivity for fractional-order systems, Nonlinear Dynamics80(1–2): 287–294.10.1007/s11071-014-1868-1Search in Google Scholar

Wirtz, D., Sorensen, D. C. and Haasdonk, B. (2014). A posteriori error estimation for deim reduced nonlinear dynamical systems, SIAM Journal on Scientific Computing36(2): A311–A338.10.1137/120899042Search in Google Scholar

eISSN:
2083-8492
Idioma:
Inglés
Calendario de la edición:
4 veces al año
Temas de la revista:
Mathematics, Applied Mathematics