Strictly convex loss functions for port-Hamiltonian based optimization algorithm for MTDC networks

@article{Benedito2016StrictlyCL,
  title={Strictly convex loss functions for port-Hamiltonian based optimization algorithm for MTDC networks},
  author={Ernest Benedito and Dunstano del Puerto-Flores and Arnau D{\`o}ria-Cerezo and Olivier van der Feltz and Jacquelien M. A. Scherpen},
  journal={2016 IEEE 55th Conference on Decision and Control (CDC)},
  year={2016},
  pages={7483-7488}
}
In this work we propose a primal-dual method that can be cast in a port-Hamiltonian framework for minimizing the power losses in a multi-terminal DC network. The main contribution consists of proposing an alternative power loss function by means of a change of variables that translates the convex objective function into a strictly convex objective function. The results hold under some restrictive assumptions, but necessary to make steps towards a complete algorithm in future research. The… CONTINUE READING

Citations

Publications citing this paper.

References

Publications referenced by this paper.
SHOWING 1-10 OF 17 REFERENCES