论文信息 - Parametric Model Order Reduction of Port-Hamiltonian Systems by Matrix Interpolation

Parametric Model Order Reduction of Port-Hamiltonian Systems by Matrix Interpolation

Abstract In this paper, parametric model order reduction of linear time-invariant systems by matrix interpolation is adapted to large-scale systems in port-Hamiltonian form. A new weighted matrix interpolation of locally reduced models is introduced in order to preserve the port-Hamiltonian structure, which guarantees the passivity and stability of the interpolated system. The performance of the new method is demonstrated by technical examples.

[1] Eric James Grimme,et al. Krylov Projection Methods for Model Reduction , 1997 .

[2] Boris Lohmann,et al. Parametric Model Order Reduction by Matrix Interpolation , 2010, Autom..

[3] Thomas Wolf,et al. Passivity and Structure Preserving Order Reduction of Linear Port-Hamiltonian Systems Using Krylov Subspaces , 2010, Eur. J. Control.

[4] Thomas Wolf,et al. Stability-preserving parametric model reduction by matrix interpolation , 2011 .

[5] Arjan van der Schaft,et al. Structure-preserving tangential interpolation for model reduction of port-Hamiltonian systems , 2011, Autom..

[6] Alessandro Astolfi,et al. Moment matching for linear port Hamiltonian systems , 2011, IEEE Conference on Decision and Control and European Control Conference.

[7] Athanasios C. Antoulas,et al. Approximation of Large-Scale Dynamical Systems , 2005, Advances in Design and Control.

[8] R. Freund. Krylov-subspace methods for reduced-order modeling in circuit simulation , 2000 .

[9] Arjan van der Schaft,et al. Structure preserving model reduction of port-Hamiltonian systems by moment matching at infinity , 2010, Autom..

[10] Diana Bohm,et al. L2 Gain And Passivity Techniques In Nonlinear Control , 2016 .

[11] Boris Lohmann,et al. How to choose a single expansion point in Krylov-based model reduction? , 2009 .