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Port-Hamiltonian Dynamic Mode Decomposition

Riccardo Morandin, Jonas Nicodemus, Benjamin Unger

2023SIAM Journal on Scientific Computing19 citationsDOI

Abstract

.We present a novel physics-informed system identification method to construct a passive linear time-invariant system. In more detail, for a given quadratic energy functional, measurements of the input, state, and output of a system in the time domain, we find a realization that approximates the data well while guaranteeing that the energy functional satisfies a dissipation inequality. To this end, we use the framework of port-Hamiltonian (pH) systems and modify the dynamic mode decomposition, respectively, operator inference, to be feasible for continuous-time pH systems. We propose an iterative numerical method to solve the corresponding least-squares minimization problem. We construct an effective initialization of the algorithm by studying the least-squares problem in a weighted norm, for which we present the analytical minimum-norm solution. The efficiency of the proposed method is demonstrated with several numerical examples.Keywordsdynamic mode decompositionport-Hamiltonian systemssystem identificationdissipation inequalitypassivityknowledge-driven realizationMSC codes37J0637M9965P1093A3093B3093C05

Topics & Concepts

MathematicsInitializationQuadratic equationNorm (philosophy)Applied mathematicsMathematical optimizationHamiltonian (control theory)AlgorithmComputer scienceProgramming languagePolitical scienceGeometryLawModel Reduction and Neural NetworksControl and Stability of Dynamical SystemsAdvanced Electron Microscopy Techniques and Applications
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