# Numerical methods to compute a minimal realization of a port-Hamiltonian system

## TL;DR

This paper introduces three numerical algorithms for deriving port-Hamiltonian models from time-domain input-output data, enhancing the tools available for modeling complex multi-physics systems.

## Contribution

It presents novel indirect numerical methods for realizing port-Hamiltonian systems from data, with implementations and numerical examples demonstrating their effectiveness.

## Key findings

- Algorithms successfully derive pH models from data
- Methods are implemented in MATLAB
- Numerical examples validate the approaches

## Abstract

Port-Hamiltonian (pH) systems are a very important modeling tool in almost all areas of systems and control, in particular in network based model of multi-physics multi-scale systems. They lead to remarkably robust models that can be easily interconnected. This paper discusses the derivation of pH models from time-domain input-output data. While a direct construction of pH models is still an open problem, we present three different indirect numerical methods for the realization of pH systems. The algorithms are implemented in MATLAB and their performance is illustrated via several numerical examples.