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On the Control of Multi-Agent Systems: A Survey

机译:关于多机构系统的控制:一项调查

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Recent years have witnessed a trend to use networked multiple autonomous agents to accomplish complex tasks arising from space-based applications, smart grids, and machine learning. Such systems are referred to as multi-agent systems, where a global objective is achieved via the local interactions among the agents. The recent two decades have witnessed a rapid development of MASs in automatic control, but their root can be traced back much earlier. This paper reviews the research progress of MASs in past years. After briefly introducing the basic concepts and definitions, we discuss agents' dynamic models, including both linear and nonlinear models, describe different cooperating tasks, such as consensus, coordinating tracking, formation control, distributed average tracking, distributed estimation, containment control, surrounding control, and distributed optimization. We introduce various research issues for MASs, including time-delays, noise or disturbance, quantization, connectivity maintenance, and event-triggered control. We present different MAS control algorithms, including proportional control, proportional-integral control, adaptive control, model predictive control, passivity-based control, and nonsmooth control, and their applications in multi-robot systems, sensor networks, smart grid, machine learning, social networks, and many-core microprocessors.
机译:近年来,人们见证了使用网络的多个自主代理来完成由空间应用,智能电网和机器学习产生的复杂任务的趋势。这样的系统被称为多代理系统,在该系统中,通过代理之间的局部互动实现了全球目标。最近的二十年来,自动控制的质量迅速发展,但它们的根源可以更早地追溯到。本文回顾了过去几年质量的研究进度。在简要介绍了基本概念和定义之后,我们讨论了代理的动态模型,包括线性和非线性模型,描述了不同的合作任务,例如共识,协调跟踪,编队控制,分布式平均跟踪,分布式跟踪,分布式估计,封装,周围控制控制,周围控制控制控制和分布式优化。我们介绍了各种质量研究问题,包括时间延迟,噪音或干扰,量化,连接性维护和事件触发的控制。我们提出了不同的MAS控制算法,包括比例控制,比例综合控制,自适应控制,模型预测控制,基于消极的控制和非滑动控制,及其在多机器人系统,传感器网络,智能电网,机器学习,机器学习,社交网络和多核微处理器。

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