CSR-EHCS(CPS), SM: Nature-inspired Control of Networked Cyber-physical Systems

CSR-EHCS(CPS)，SM：网络信息物理系统的自然启发控制

• 批准号: 0834691
• 负责人: Wei Ren
• 金额: --
• 依托单位: Utah State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2012-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0834691&HistoricalAwards=false
• 关键词: CSR; EHCS; CPS; SM; Nature

This project focuses on deriving novel control strategies, inspired by properties exhibited in nature, for networked cyber-physical systems, with specific application to networked autonomous vehicles. Many phenomena in nature cannot be explained in the framework of integer-order dynamics. Similarly, networked cyber-physical systems operating in complex environments often demonstrate non-integer-order (i.e., fractional-order) dynamics. Flocks of birds often exhibit distributed coordinated tracking behavior. Similarly, distributed discrete-time coordinated tracking strategies that are candidates for implementation on networked embedded computers are important in many applications involving networked autonomous vehicles. The thrusts of this project are (i) analysis and design of distributed strategies for coordination of networked fractional-order systems, (ii) analysis and design of distributed discrete-time coordinated tracking strategies, and (iii) experimental validation of new distributed strategies on teams of networked ground robots and unmanned aerial vehicles (UAVs). Specifically, the PI will analyze and design distributed coordination strategies for networked fractional differential equations and derive an optimal coordination strategy with varying fractional orders. The PI will also address the theoretical challenges of distributed discrete-time coordinated tracking in the presence of dynamic network topology, time delay, asynchronous interaction, and information feedback. The research is expected to lead to new thinking about networked cyber-physical systems operating in complex environments, provide coordination schemes accounting for real-world constraints, and help bridge the gap between theory and applications in distributed coordination of networked autonomous vehicles. The research has impact on numerous civilian, homeland security, and military applications involving networked cyber-physical systems. Examples include precision agriculture, automated mining, environmental monitoring, border patrol, surveillance, and reconnaissance. On the education side, the PI will mentor and educate undergraduate and graduate students through his research, a yearly Sumo Robot competition, and the Utah State University Robotics Club. The project will also provide research experience for K-12 teachers and students.

该项目的重点是推导出新的控制策略，灵感来自于自然界中展示的属性，用于网络网络物理系统，并具体应用于网络自动驾驶汽车。自然界中的许多现象不能用整级动力学的框架来解释。类似地，在复杂环境中运行的网络化网络物理系统通常表现出非整数阶（即分数阶）动态。鸟群经常表现出分布式的协调跟踪行为。类似地，分布式离散时间协调跟踪策略是在联网嵌入式计算机上实现的候选策略，在涉及联网自动驾驶汽车的许多应用中非常重要。该项目的重点是(i)分析和设计用于网络分数阶系统协调的分布式策略，（ii）分析和设计分布式离散时间协调跟踪策略，以及（iii）对网络地面机器人和无人驾驶飞行器（uav）团队的新分布式策略进行实验验证。具体而言，PI将分析和设计网络分数阶微分方程的分布式协调策略，并推导出不同分数阶的最优协调策略。PI还将解决在动态网络拓扑、时间延迟、异步交互和信息反馈存在下的分布式离散时间协调跟踪的理论挑战。该研究有望引发在复杂环境中运行的网络网络物理系统的新思维，提供考虑现实世界约束的协调方案，并有助于弥合网络自动驾驶汽车分布式协调理论与应用之间的差距。该研究对涉及网络信息物理系统的众多民用、国土安全和军事应用产生了影响。例子包括精准农业、自动化采矿、环境监测、边境巡逻、监视和侦察。在教育方面，PI将通过他的研究、一年一度的相扑机器人比赛和犹他州立大学机器人俱乐部来指导和教育本科生和研究生。该项目还将为K-12教师和学生提供研究经验。