Distributed Identification of Contracting and/or Monotone Network Dynamics
Abstract
This paper proposes methods for identification of large-scale networked systems with guarantees that the resulting model will be contracting -- a strong form of nonlinear stability -- and/or monotone, i.e. order relations between states are preserved. The main challenges that we address are: simultaneously searching for model parameters and a certificate of stability, and scalability to networks with hundreds or thousands of nodes. We propose a model set that admits convex constraints for stability and monotonicity, and has a separable structure that allows distributed identification via the alternating directions method of multipliers (ADMM). The performance and scalability of the approach is illustrated on a variety of linear and non-linear case studies, including a nonlinear traffic network with a 200-dimensional state space.
Cite
@article{arxiv.2107.14309,
title = {Distributed Identification of Contracting and/or Monotone Network Dynamics},
author = {Max Revay and Jack Umenberger and Ian R. Manchester},
journal= {arXiv preprint arXiv:2107.14309},
year = {2021}
}
Comments
Preprint of full paper accepted for publication in IEEE Trans. Automatic Control