Distributed Identification of Contracting and/or Monotone Network Dynamics

• URL: http://arxiv.org/abs/2107.14309v1
• Date: Thu, 29 Jul 2021 20:15:02 GMT
• Title: Distributed Identification of Contracting and/or Monotone Network Dynamics
• Authors: Max Revay, Jack Umenberger, Ian R. Manchester
• Abstract summary: This paper proposes methods for identification of large-scale networked systems with guarantees that the resulting model will be contracting. 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.
• Score: 8.057006406834466
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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