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Distributed Adaptive Optimization for Generalized Linear Multiagent Systems

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  • Shuxin Liu
  • Haijun Jiang
  • Liwei Zhang
  • Xuehui Mei

Abstract

In this paper, the edge-based and node-based adaptive algorithms are established, respectively, to solve the distribution convex optimization problem. The algorithms are based on multiagent systems with general linear dynamics; each agent uses only local information and cooperatively reaches the minimizer. Compared with existing results, a damping term in the adaptive law is introduced for the adaptive algorithms, which makes the algorithms more robust. Under some sufficient conditions, all agents asymptotically converge to the consensus value which minimizes the cost function. An example is provided for the effectiveness of the proposed algorithms.

Suggested Citation

  • Shuxin Liu & Haijun Jiang & Liwei Zhang & Xuehui Mei, 2019. "Distributed Adaptive Optimization for Generalized Linear Multiagent Systems," Discrete Dynamics in Nature and Society, Hindawi, vol. 2019, pages 1-10, August.
    • Handle: RePEc:hin:jnddns:9181093
    DOI: 10.1155/2019/9181093
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