"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: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=509333
• 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.

这项研究涉及由多个相互作用子系统组成的多代理系统的控制。 我们专注于通过影响系统代理的单独控制剂引入控制的问题。 这种类型的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，控制代理人是警官），军事领导人指挥车辆（系统代理是车辆和车辆，控制代理人是领导者），环保主义者试图吸引公司采用“绿色”技术（系统代理是公司，而控制代理是激进主义者）。 这种类型的技术系统的示例包括分布式能源系统，其中成千上万的电力来源而不是少数大型电力与电网相连（系统代理是发电机，控制剂是电压/相/相/电源控制器）和自动流量系统（系统代理是交通信号灯，控制代理是交通控制器）。 原则上，所有这些系统都可以数学上进行建模，并且可以设计控制剂的控制规则。 由于所讨论的系统的复杂性，分散的框架很有吸引力。 但是，即使是分散的控制器，设计和实践中的部署也很快变得非常复杂。 我们旨在通过使用我们开发的称为Targeting的新方法来应对这种复杂性，其中每个控制剂都将注意力集中在单个，精心选择的系统代理上。 这项研究的主要贡献是，基于现有知识和通过本提案创建的知识的严格理论用于确定应使用多少控制代理，应放置在哪里，应该将其各自的目标是什么以及应使用哪些控制信号成功控制所有系统代理。 目前，这种信息通常是无法科学的，因此仅仅导致对直觉或经验的依赖。 通过这笔资金，总共有10名研究生将得到部分支持。