Low-Rank LQR Optimal Control Design for Controlling Distributed Multi-Agent Systems
Low-Rank LQR Optimal Control Design for Controlling Distributed Multi-Agent Systems
复制标题
控制分布式多智能体系统的低秩 LQR 最优控制设计
DOI：
--
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
M. Rasouli
中科院分区：
文献类型：
--
作者：
Myung;A. Abdallah;M. Rasouli
本文采用线性二次型调节器（LQR）方法研究了多智能体分布式控制系统的最优控制设计问题。为了有效地控制大型分布式系统，如智能电网和多智能体机器人系统，设计考虑到各种通信约束（如有限功率、有限能量或有限通信带宽）的反馈控制器至关重要。本文主要研究无线通信网络中LQR最优控制设计中的通信能量降低问题。由于射频（Radio Frequency， RF）信号可以以广播的方式向各个方向传播，我们利用这一特性建立了一种低秩LQR最优控制模型，该模型可以显著降低分布式反馈控制系统中的通信能量。为了解决这个问题，我们提出了一种基于乘法器交替方向法（ADMM）的算法。通过数值实验，我们证明了采用低秩结构设计的反馈控制器在能量消耗方面优于以往仅关注减少网络中通信链路数量的稀疏LQR最优控制设计
This paper addresses the problem of optimal control design for distributed control systems with multiple agents, using a Linear Quadratic Regulator (LQR) approach. To effectively control large-scale distributed systems, such as smart-grid and multi-agent robotic systems, it is crucial to design feedback controllers that take into account the various communication constraints, such as limited power, limited energy, or limited communication bandwidth. In this work, we focus on reducing the communication energy in LQR optimal control design on wireless communication networks. Since the Radio Frequency (RF) signal can spread in all directions in a broadcast way, we take advantage of this characteristic to formulate a low-rank LQR optimal control model that can significantly reduce communication energy in distributed feedback control systems. To solve the problem, we propose an algorithm based on the Alternating Direction Method of Multipliers (ADMM). Through numerical experiments, we demonstrate that a feedback controller designed using low-rank structure can outperform the previous work on sparse LQR optimal control design, which only focused on reducing the number of communication links in a network, in terms of energy consumption