Efficient Computation of H2 Performance on Series-Parallel Networks
Optimization and Control
2020-04-28 v3
Abstract
Series-parallel networks are a class of graphs on which many NP-hard problems have tractable solutions. In this paper, we examine performance measures on leader-follower consensus on series-parallel networks. We show that a distributed computation of the norm can be done efficiently on this system by exploiting a decomposition of the network into atomic elements and composition rules. Lastly, we examine the problem of adaptively re-weighting the network to optimize the norm, and show that it can be done with similar complexity.
Cite
@article{arxiv.1903.05325,
title = {Efficient Computation of H2 Performance on Series-Parallel Networks},
author = {Mathias Hudoba de Badyn and Mehran Mesbahi},
journal= {arXiv preprint arXiv:1903.05325},
year = {2020}
}
Comments
6 pages, 5 figures. To appear in proceedings of the 2019 American Control Conference