Dissipativity-Based Distributed Stability Analysis for Networks with Heterogeneous Nonlinear Agents

Fuente: arXiv
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Autores principales: Jang, Ingyu, LoCicero, Ethan J., Bridgeman, Leila
Formato: Preprint
Publicado: 2025
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author Jang, Ingyu
LoCicero, Ethan J.
Bridgeman, Leila
author_facet Jang, Ingyu
LoCicero, Ethan J.
Bridgeman, Leila
contents Stabilizing large networks of nonlinear agents is challenging; decomposition and distributed analysis of these networks are crucial for computational tractability and information security. Vidyasagar's Network Dissipativity Theorem enables both properties concurrently in distributed network analysis. This paper explored combining it with the alternating direction methods of multipliers to develop distributed stability analysis for networks of inhomogeneous, nonlinear agents. One algorithm enhances information security by requiring agents to share only a dissipativity characterization, not a dynamical model, for stability analysis. A second algorithm further restricts this information sharing to their clique, thereby enhancing security, and can also reduce the computational burden of stability analysis if the network allows chordal decomposition. The convergence of the proposed algorithms is demonstrated, and criteria are identified for decomposable networks facilitating chordal decomposition. The effectiveness of the proposed methods is demonstrated through numerical examples involving a swarm of linearized unmanned aerial vehicles and networks beyond linear time-invariant agents.
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publishDate 2025
record_format arxiv
spellingShingle Dissipativity-Based Distributed Stability Analysis for Networks with Heterogeneous Nonlinear Agents
Jang, Ingyu
LoCicero, Ethan J.
Bridgeman, Leila
Systems and Control
Optimization and Control
Stabilizing large networks of nonlinear agents is challenging; decomposition and distributed analysis of these networks are crucial for computational tractability and information security. Vidyasagar's Network Dissipativity Theorem enables both properties concurrently in distributed network analysis. This paper explored combining it with the alternating direction methods of multipliers to develop distributed stability analysis for networks of inhomogeneous, nonlinear agents. One algorithm enhances information security by requiring agents to share only a dissipativity characterization, not a dynamical model, for stability analysis. A second algorithm further restricts this information sharing to their clique, thereby enhancing security, and can also reduce the computational burden of stability analysis if the network allows chordal decomposition. The convergence of the proposed algorithms is demonstrated, and criteria are identified for decomposable networks facilitating chordal decomposition. The effectiveness of the proposed methods is demonstrated through numerical examples involving a swarm of linearized unmanned aerial vehicles and networks beyond linear time-invariant agents.
title Dissipativity-Based Distributed Stability Analysis for Networks with Heterogeneous Nonlinear Agents
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2511.13925