Optimal design of stochastic networked control systems

随机网络控制系统的优化设计

• 批准号: 355788-2013
• 负责人: Yuksel, Serdar
• 金额: $ 1.75万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=572656
• 关键词: Optimal; design; stochastic; networked; control

The goal of the proposed research is to advance the understanding of networked and cooperative control systems under uncertainty and information constraints. Stochastic networked control systems arise in many practical settings (such as in decentralized and adaptive power regulation in the energy/power grid, automotive applications for collision avoidance, sensor networks and in economics theory). However, there are many fundamental and practical aspects yet to be understood regarding such systems. The proposed research will have three main technical and practical contributions: (i) Development of a quantitative theory on the performance of decentralized dynamic systems given information constraints. This will lead to design principles for practical systems and infrastructure design for a large variety of applications. (ii) Stochastic stability of complex connected systems through event-driven communications and development of stochastic drift criteria for stability of such systems. This is important for decentralized systems which can only communicate when resources are available. (iii) Generation of approximately optimal control policies when controllers are able to learn the dynamics of a system through partial information or training sequences. This is especially important in cognition and learning aspects of controllers for adapting to an unknown environment in which they live and act. The outcomes will allow for the design of adaptive, cognitive and resource-efficient decentralized and networked control systems. In addition to fundamental contributions on theoretical problems regarding decision making under uncertainty, the research outcomes will have important practical impact in the technology sector in Canada and beyond, in view of optimal engineering system design for networked control systems under information constraints. In addition, four PhD, two MSc and two undergraduate students will be trained rigorously under this proposal, and be independent researchers who will benefit Canada's research and technological community.

本文的研究目的是加深对不确定性和信息约束下的网络化协同控制系统的理解。随机网络控制系统出现在许多实际环境中(如能源/电网中的分散和自适应功率调节、汽车防撞应用、传感器网络和经济学理论)。然而，关于这类系统，还有许多基本和实际的方面有待了解。这项拟议的研究将有三个主要的技术和实际贡献：(I)发展一种关于信息约束下分散动态系统性能的定量理论。这将导致实际系统的设计原则和各种应用的基础设施设计。(2)通过事件驱动通信实现复杂关联系统的随机稳定性，并发展这类系统稳定性的随机漂移准则。这对于分散的系统很重要，因为只有在资源可用时才能进行通信。(Iii)当控制器能够通过部分信息或训练序列学习系统的动态时，产生近似最优控制策略。这在控制器的认知和学习方面尤其重要，以适应他们生活和行动的未知环境。 结果将有助于设计适应性、认知性和资源效率高的分散和联网控制系统。除了对不确定条件下决策理论问题的基础性贡献外，该研究成果还将对信息约束下的网络控制系统的优化工程系统设计在加拿大及其他地区的技术领域产生重要的实践影响。此外，根据这项提议，四名博士、两名硕士和两名本科生将接受严格的培训，他们是独立的研究人员，将使加拿大的研究和技术界受益。