# Model reduction techniques for linear constant coefficient port-Hamiltonian differential-algebraic systems

@inproceedings{Hauschild2019ModelRT, title={Model reduction techniques for linear constant coefficient port-Hamiltonian differential-algebraic systems}, author={Sarah-Alexa Hauschild and Nicole Marheineke and Volker Mehrmann}, year={2019} }

Port-based network modeling of multi-physics problems leads naturally to a formulation as port-Hamiltonian differential-algebraic 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 space-discretized partial differential-algebraic system, in optimization and control there is a need for model reduction methods that preserve the port-Hamiltonian… CONTINUE READING

Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

1

Twitter Mention

#### Citations

##### Publications citing this paper.

SHOWING 1-3 OF 3 CITATIONS

## Structure-preserving Interpolatory Model Reduction for Port-Hamiltonian Differential-Algebraic Systems

VIEW 5 EXCERPTS

CITES BACKGROUND & METHODS

HIGHLY INFLUENCED

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

VIEW 2 EXCERPTS

CITES BACKGROUND & METHODS

#### References

##### Publications referenced by this paper.

SHOWING 1-10 OF 36 REFERENCES

## Linear port-Hamiltonian descriptor systems

VIEW 8 EXCERPTS

## Differential-Algebraic Equations

VIEW 4 EXCERPTS

HIGHLY INFLUENTIAL

## LARGE-SCALE COMPUTATION OF L∞-NORMS BY A GREEDY

VIEW 1 EXCERPT