"Decentralized Regulation, Tracking, and Disturbance Rejection for Multi-agent Systems: A Targeting Approach"

“多智能体系统的去中心化监管、跟踪和抗扰：一种目标方法”

• 批准号: 238743-2012
• 负责人: Davison, Daniel
• 金额: $ 1.31万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=547076
• 关键词: Decentralized; Regulation; Tracking; Disturbance; Rejection

This research deals with the control of multi-agent systems, that is, systems that are composed of multiple interacting subsystems. We focus on problems in which control is introduced through separate control agents that influence the system agents. Examples of socio-economic systems of this type include police officers trying to control a crowd (where the system agents are people in the crowd and the control agents are officers), military leaders directing a field of vehicles (where the system agents are vehicles and the control agents are leaders), and environmentalists trying to entice companies to adopt "green" technology (where the system agents are companies and the control agents are activists). Examples of technological systems of this type include distributed energy systems, in which thousands of small sources of electricity, rather than a few large ones, are connected to the power grid (where the system agents are generators and the control agents are voltage/phase/power controllers) and automated traffic systems (where the system agents are traffic lights and the control agents are traffic controllers). All of these systems can, in principle, be modelled mathematically and control rules for the control agents can be devised. Due to the complexity of the systems in question, a decentralized framework is appealing. However, even decentralized controllers can quickly become overwhelmingly complicated to design and, in practice, to deploy. We aim to deal with this complexity by using a new approach we have developed called targeting, wherein each of the control agents focuses attention on a single, carefully chosen, system agent. The major contribution of this research is that rigorous theory, based on both existing knowledge and the knowledge created through this proposal, is used to determine how many control agents should be used, where they should be placed, what their respective targets should be, and what control signals should be used to successfully control all of the system agents. At present, such information is often unavailable scientifically, leading to dependence on intuition or experience alone. A total of 10 graduate students will be partially supported through this funding.

本研究探讨多智能体系统的控制，即由多个相互作用的子系统组成的系统。 我们专注于通过单独的控制代理，影响系统代理引入控制的问题。 这类社会经济系统的例子包括试图控制人群的警察（系统代理是人群中的人，控制代理是军官），指挥车辆的军事领导人（其中系统代理是车辆，控制代理是领导者），以及试图诱使公司采用“绿色”技术的环保主义者（其中系统代理人是公司，控制代理人是活动家）。 这种类型的技术系统的例子包括分布式能源系统，其中数千个小电源而不是几个大电源连接到电网（其中系统代理是发电机，控制代理是电压/相位/功率控制器）和自动交通系统（其中系统代理是交通灯，控制代理是交通控制器）。 原则上，所有这些系统都可以进行数学建模，并且可以设计用于控制代理的控制规则。 由于所讨论的系统的复杂性，去中心化的框架是有吸引力的。 然而，即使是分散的控制器也会很快变得非常复杂，设计和部署起来也会非常复杂。 我们的目标是处理这种复杂性，通过使用一种新的方法，我们已经开发了所谓的目标，其中每个控制代理集中注意力在一个单一的，精心挑选的，系统代理。 这项研究的主要贡献是，严格的理论，基于现有的知识和知识，通过这个建议，是用来确定应该使用多少控制代理，他们应该被放置在哪里，他们各自的目标应该是什么，以及什么控制信号应该被用来成功地控制所有的系统代理。 目前，这种信息往往无法从科学角度获得，导致只能依赖直觉或经验。 共有10名研究生将通过这笔资金得到部分支持。