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arXiv 1902.00865math.OCcs.SYeess.SY
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分布式最优稳态调节用于具有外部扰动的高阶多智能体系统

Distributed Optimal Steady-State Regulation for High-Order Multi-Agent Systems with External Disturbances

School of Automation, Beijing University of Posts and Telecommunications(北京邮电大学自动化学院)

Yutao Tang

AI总结:

本文研究了具有外部扰动的异构线性多智能体系统的分布式最优稳态调节问题,通过嵌入式控制设计将问题转化为两个更简单的子问题,并在温和假设下提出状态反馈和输出反馈控制方法,进一步扩展到仅使用实时梯度信息的情况,通过数值模拟验证了有效性。

摘要:

本文提出并研究了针对受外部扰动影响的异构线性多智能体系统的分布式最优稳态调节问题。我们的目标是将这种高阶多智能体网络引导至由资源分配问题的分布式最优解确定的预设稳态。为了解决这个问题,我们采用嵌入式控制设计,将该问题转化为两个更简单的子问题。然后,在温和假设下,提出状态反馈和输出反馈控制方法以解决该问题并实现扰动抑制。此外,我们通过高增益控制技术将这些结果扩展到仅使用实时梯度信息的情况。最后,数值模拟验证了其有效性。

英文摘要:

In this paper, a distributed optimal steady-state regulation problem is formulated and investigated for heterogeneous linear multi-agent systems subject to external disturbances. We aim to steer this high-order multi-agent network to a prescribed steady-state determined as the optimal solution of a resource allocation problem in a distributed way. To solve this problem, we employ an embedded control design and convert the formulated problem to two simpler subproblems. Then, both state-feedback and output feedback controls are presented under mild assumptions to solve this problem with disturbance rejection. Moreover, we extend these results to the case with only real-time gradient information by high-gain control techniques. Finally, numerical simulations verify their effectiveness.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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