Synchronization control of unknown heterogeneous multi-agent system via model-free adaptive dynamic programming

Lina XIA; Qing LI; Ruizhuo SONG; Zihan WANG; Zhen XU

doi:10.11959/j.issn.2096-6652.202143

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Synchronization control of unknown heterogeneous multi-agent system via model-free adaptive dynamic programming

Special Column: Data Based Learning and Optimization | 更新时间：2024-06-05

- Synchronization control of unknown heterogeneous multi-agent system via model-free adaptive dynamic programming
- Chinese Journal of Intelligent Science and Technology Vol. 3, Issue 4, Pages: 444-448(2021)
- 作者机构：
  
  1. 北京科技大学自动化学院，北京 100083
  2. 北京科技大学城镇化与城市安全研究院，北京 100083
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-6652.202143
  CLC： TP18
- Published Online：2021-12，
  
  Published：15 December 2021
- 稿件说明：
移动端阅览
Lina XIA, Qing LI, Ruizhuo SONG, et al. Synchronization control of unknown heterogeneous multi-agent system via model-free adaptive dynamic programming[J]. Chinese journal of intelligent science and technology, 2021, 3(4): 444-448.
DOI：

Lina XIA, Qing LI, Ruizhuo SONG, et al. Synchronization control of unknown heterogeneous multi-agent system via model-free adaptive dynamic programming[J]. Chinese journal of intelligent science and technology, 2021, 3(4): 444-448. DOI： 10.11959/j.issn.2096-6652.202143.

摘要

多智能体协同在众多领域逐渐得到应用，但是还有很多仍未解决的问题。为此，研究了基于无模型自适应动态规划（MFADP）的未知异构多智能体系统同步控制问题，其中领航者智能体和追随者智能体动态模型均是未知的。首先为每一个追随者智能体设计观测器来估计领航者智能体的信息，包括领航者智能体状态以及领航者智能体系统动态矩阵。然后利用追随者智能体动态模型信息和观测器动态模型信息构建增广系统，运用贝尔曼最优性原理求得最优控制器以及对应的代数黎卡提方程。在追随者智能体系统动态模型信息未知的情况下，引出了MFADP算法。最后使用双质量-弹簧系统来验证所提算法的有效性。

Abstract

Synchronization of multi-agent system has been gradually applied in the most fields

but there are still many unsolved problems.The synchronization control of unknown heterogeneous multi-agent system based on model-free adaptive dynamic programming (MFADP) algorithm was studied.Firstly

an observer was designed for each follower to estimate the information of the leader

including the state and the system dynamic matrix of the leader.Then

the optimal controller was obtained by exploiting the Bellman optimality principle.Under the condition that the dynamics of the follower was unknown

a MFADP algorithm was proposed.Finally

two-mass-spring systems were used to verify the effectiveness of the algorithm.

关键词

Keywords

references

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