Layered Control Architectures for Complex Networked Systems

复杂网络系统的分层控制架构

• 批准号: 0122412
• 负责人: Mark Spong
• 金额: $ 27万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0122412&HistoricalAwards=false
• 关键词: Layered; Control; Architectures; Complex; Networked

Future embedded real time control systems will increasingly be wireless, distributed, large-scale, and will be inherently hybrid, combining discrete or digital components with continuous time nonlinear dynamics. The complexity of such networked systems presents new challenges that lie at the confluence of communication, computing, and control. In this proposal we will investigate the design and analysis of networked real-time control systems treating complexity, delays, reliability, and other issues. Our goal is to develop control strategies for networked control systems that are application independent and enable the convergence of sensing and actuation with communication and computing. Potential applications of our results include autonomous vehicles and autonomous locomotion systems, remote construction, remote surgery, work in hazardous and remote environments, surveillance, search and rescue robots, haptic devices, and distance education. Our research will focus on the development of new theoretical tools for analysis and control of networked systems with time-varying delays. On the implementation side, we will develop proof-of concept type experiments on in-house designed and built systems, including networks of remotely controllable cars and robots.

未来的嵌入式真实的时间控制系统将越来越多地是无线的、分布式的、大规模的，并且将是固有的混合的，将离散或数字组件与连续时间非线性动态相结合。 此类网络系统的复杂性带来了通信、计算和控制交汇处的新挑战。 在这个建议中，我们将研究网络实时控制系统的设计和分析，处理复杂性，延迟，可靠性和其他问题。 我们的目标是为网络控制系统开发控制策略，这些控制策略是独立于应用程序的，并且能够将传感和驱动与通信和计算融合在一起。 我们的研究结果的潜在应用包括自动驾驶汽车和自动运动系统，远程施工，远程手术，在危险和远程环境中工作，监视，搜索和救援机器人，触觉设备和远程教育。 我们的研究将集中在发展新的理论工具，分析和控制的网络系统的时变延迟。 在实施方面，我们将在内部设计和建造的系统上开发概念验证型实验，包括远程可控汽车和机器人网络。