利用量化八卦型子梯度算法实现几乎确定的最优一致性

Hu Bin, Jiang Xiao-Wei, Zhang Ding-xue, Li Tao, Guan Zhi-hong
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引用次数: 0

摘要

研究了不完全通信条件下多智能体网络的最优共识问题。针对网络问题,我们采用标准八卦算法与子梯度方法相结合的多智能体协同控制方案。在该控制策略下,智能体通过量化机制传递需要的信息,并采用抖动技术处理引发的量化误差。采用随机逼近法进行了详细的收敛性分析。结果表明,在该算法下,通过量化通信,多智能体网络几乎可以达到最优一致性。进一步进行了相关的仿真工作,验证了推导出的理论结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Realize almost sure optimal consensus with quantized gossip-type subgradient algorithms
This paper concerns with the optimal consensus problem of multi-agent networks under imperfect communication. With the network issues, we resort to an integrated scheme of the standard gossip algorithm and the subgradient method for multiagent cooperative control. Under the proposed control strategy, agents are supposed to transfer desirable information through a quantized mechanism, and the dithering technique is adopted to deal with the triggered quantization errors. Detailed convergence analysis is carried out by the stochastic approximation method. It is demonstrated that multi-agent networks can achieve almost sure optimal consensus under the proposed algorithm through quantized communication. Related simulation work is further given to validate the derived theoretical results.
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