Model reduction techniques for linear constant coefficient portHamiltonian differentialalgebraic systems
Abstract
Portbased network modeling of multiphysics problems leads naturally to a formulation as portHamiltonian differentialalgebraic system. In this way, the physical properties are directly encoded in the structure of the model. Since the state space dimension of such systems may be very large, in particular when the model is a spacediscretized partial differentialalgebraic system, in optimization and control there is a need for model reduction methods that preserve the portHamiltonian structure while keeping the (explicit and implicit) algebraic constraints unchanged. To combine model reduction for differentialalgebraic equations with portHamiltonian structure preservation, we adapt two classes of techniques (reduction of the Dirac structure and moment matching) to handle portHamiltonian differentialalgebraic equations. The performance of the methods is investigated for benchmark examples originating from semidiscretized flow problems and mechanical multibody systems.
 Publication:

arXiv eprints
 Pub Date:
 January 2019
 arXiv:
 arXiv:1901.10242
 Bibcode:
 2019arXiv190110242H
 Keywords:

 Mathematics  Optimization and Control;
 Mathematics  Dynamical Systems;
 Mathematics  Numerical Analysis;
 34H05;
 41A22;
 65L80;
 93A15;
 65F22