Communication- and Control-Aware Optimal Quantizer Selection for Multi-Agent Control

IF 2.4 Q2 AUTOMATION & CONTROL SYSTEMS
Mohammad Afshari;Dipankar Maity;Panagiotis Tsiotras
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Abstract

We consider a multi-agent linear quadratic optimal control problem. Due to communication constraints, the agents are required to quantize their local state measurements before communicating them to the rest of the team, thus resulting in a decentralized information structure. The optimal controllers are to be synthesized under this decentralized and quantized information structure. The agents are given a set of quantizers with varying quantization resolutions—higher resolution incurs higher communication cost and vice versa. The team must optimally select the quantizer to prioritize agents with ‘high-quality’ information for optimizing the control performance under communication constraints. We show that there exist a separation between the optimal solution to the control problem and the choice of the optimal quantizer. We show that the optimal controllers are linear and the optimal selection of the quantizers can be determined by solving a linear program.
面向多代理控制的通信和控制感知最优量化器选择
我们考虑的是一个多代理线性二次优化控制问题。由于通信限制,各代理在将其本地状态测量信息传递给团队其他成员之前,必须对其进行量化,从而形成一种分散的信息结构。最优控制器就是在这种分散和量化的信息结构下合成的。代理将获得一组量化分辨率各不相同的量化器--分辨率越高,通信成本越高,反之亦然。在通信限制条件下,团队必须优化选择量化器,优先考虑拥有 "高质量 "信息的代理,以优化控制性能。我们证明,控制问题的最优解与最优量化器的选择之间存在分离。我们证明,最优控制器是线性的,而量化器的最优选择可以通过求解线性程序来确定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Control Systems Letters
IEEE Control Systems Letters Mathematics-Control and Optimization
CiteScore
4.40
自引率
13.30%
发文量
471
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