Consensus-Based Stability Analysis of Multi-Agent Networks
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866914168099045376 |
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| author | Jang, Ingyu LoCicero, Ethan J. Bridgeman, Leila |
| author_facet | Jang, Ingyu LoCicero, Ethan J. Bridgeman, Leila |
| contents | The emergence of large-scale multi-agent systems has led to controller synthesis methods for sparse communication between agents. However, most sparse controller synthesis algorithms remain centralized, requiring information exchange and high computational costs. This underscores the need for distributed algorithms that design controllers using only local dynamics information from each agent. This paper presents a consensus-based distributed stability analysis. The proposed stability analysis algorithms leverage Vidyasagar's Network Dissipativity Theorem and the alternating direction methods of multipliers to perform general stability analysis. Numerical examples involving a 2D swarm of unmanned aerial vehicles demonstrate the convergence of the proposed algorithms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_13926 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Consensus-Based Stability Analysis of Multi-Agent Networks Jang, Ingyu LoCicero, Ethan J. Bridgeman, Leila Systems and Control Optimization and Control The emergence of large-scale multi-agent systems has led to controller synthesis methods for sparse communication between agents. However, most sparse controller synthesis algorithms remain centralized, requiring information exchange and high computational costs. This underscores the need for distributed algorithms that design controllers using only local dynamics information from each agent. This paper presents a consensus-based distributed stability analysis. The proposed stability analysis algorithms leverage Vidyasagar's Network Dissipativity Theorem and the alternating direction methods of multipliers to perform general stability analysis. Numerical examples involving a 2D swarm of unmanned aerial vehicles demonstrate the convergence of the proposed algorithms. |
| title | Consensus-Based Stability Analysis of Multi-Agent Networks |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2511.13926 |