CAREER: Coordination of Dynamic Networks - A Hybrid System Approach

职业：动态网络的协调 - 混合系统方法

• 批准号: 0348637
• 负责人: Rafael Fierro
• 金额: $ 40万
• 依托单位: Oklahoma State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-04-01 至 2008-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0348637&HistoricalAwards=false
• 关键词: CAREER; Coordination; Dynamic; Networks; Hybrid

This Career development plan includes significant research, educational, and outreach components. Theresearch component is focused on developing novel and systematic methodologies for the analysis, design,and implementation of cooperative dynamic networks. A dynamic network consists of spatially distributeddynamic nodes (e.g., autonomous vehicles, mobile sensors) which are coordinated by common set of goals andpossible dynamic interaction between the nodes. There are many applications where a dynamic network maybe more suitable than a single vehicle, especially where a distributed system of sensors is advantageous. Yetwithout coordinating the movement of the nodes or without managing the information the nodes retrieve,any advantage of dynamic network deployment may be lost and damaging collisions or interference mayoccur.This research will be integrated into curriculum development designed to provide research opportunitiesfor undergraduate students with emphasis on attracting and retaining underrepresented minorities. Theoutreach component will support on-going educational programs designed to target K-12 institutions, andthe Native American populations of Oklahoma.Intellectual Merit New Developments in complex networks of interacting systems like teams of au-tonomous vehicles/robots for homeland security, search and rescue operations, disaster relief operations,multi-targeting/multi-platform battlefield groups, unmanned air vehicle systems, intelligent highway/vehiclesystems, wireless surveillance networks, and elsewhere place severe demands on the design of cooperativecontrol schemes and communication strategies in the presence of changing environment. The large-scale in-terconnected nature of such systems requires logic-based supervisors with increased capabilities for dynamicplanning, optimality and that guarantees performance subject to constraints, con ict resolution, failurehandling, and other decisions. To facilitate the design of this class of systems the following key researchchallenges will be addressed: Development of computationally efficient algorithms for distributed model predictive control. Derivation of novel algorithms for cooperative optimization based control. Development new methodologies that enable goal directed sensing by fusing the information fromheterogeneous sensors over the dynamic network, and providing the required information for each nodeto plan and control its mobility. Designing adaptive robust controllers that take into account the uncertainties on the dynamics of therobotic network. Experimental verification and validation of the proposed methodologies.Broader Impact Ensuring that the above Career research thrusts have the broadest impact on society,they should be integrated with a coherent educational and outreach plan. It is well-known that robotics pro-vides an excellent platform for getting students interested in science and engineering. This proposal includeseducational components targeted at high school, undergraduate, and graduate students. The proposed workincludes: Mentoring activities that include under-represented students in Science, Mathematics, Engineering andTechnology (SMET) with the objective of retaining them in electrical and computer engineering. A robotic extension program will be designed to stimulate the interest of Native American children toincrease their appreciation and understanding of science, technology, and engineering, in an informallearning environment. Seek industrial/governmental partnerships to transfer technology. Besides publications in refereedconference and journals, new courses such as Computer Embedded Systems, Robotics and Perception,and Control Hybrid Systems will be introduced into the curriculum. Software tools, algorithms, demos and results will be available on the web.The educational and research components of this Career proposal build upon previous and on-going workand existing equipment supported by Oklahoma State University.

该职业发展计划包括重要的研究、教育和外展组成部分。研究部分专注于开发新颖且系统的方法来分析、设计和实现协作动态网络。动态网络由空间分布的动态节点（例如自动驾驶车辆、移动传感器）组成，这些节点通过共同的目标集和节点之间可能的动态交互进行协调。在许多应用中，动态网络可能比单个车辆更适合，特别是在分布式传感器系统具有优势的情况下。然而，如果不协调节点的移动或不管理节点检索的信息，动态网络部署的任何优势都可能会丧失，并且可能会发生破坏性冲突或干扰。这项研究将被纳入课程开发中，旨在为本科生提供研究机会，重点是吸引和留住代表性不足的少数群体。外展部分将支持旨在针对 K-12 机构和俄克拉荷马州美洲原住民人口的持续教育计划。 高速公路/车辆系统、无线监控网络和其他领域对环境变化下的协作控制方案和通信策略的设计提出了严格的要求。此类系统的大规模互连性质需要基于逻辑的监控器，具有增强的动态规划、优化能力，并保证性能受到约束、冲突解决、故障处理和其他决策的影响。为了促进此类系统的设计，将解决以下关键研究挑战： 开发用于分布式模型预测控制的计算高效算法。基于协作优化的控制的新颖算法的推导。开发新的方法，通过融合动态网络上异构传感器的信息，并为每个节点提供规划和控制其移动性所需的信息，实现目标定向传感。设计自适应鲁棒控制器，考虑机器人网络动力学的不确定性。对所提出的方法进行实验验证和验证。更广泛的影响确保上述职业研究主旨对社会产生最广泛的影响，应将它们与连贯的教育和推广计划相结合。众所周知，机器人技术为培养学生对科学和工程的兴趣提供了一个极好的平台。该提案包括针对高中、本科生和研究生的教育内容。拟议的工作包括： 指导活动，其中包括科学、数学、工程和技术 (SMET) 领域代表性不足的学生，目的是让他们留在电气和计算机工程领域。机器人扩展计划旨在激发美国原住民儿童的兴趣，在非正式的学习环境中提高他们对科学、技术和工程的欣赏和理解。寻求工业/政府合作伙伴关系以转让技术。除了在参考会议和期刊上发表论文外，课程中还将引入计算机嵌入式系统、机器人与感知、控制混合系统等新课程。软件工具、算法、演示和结果将在网上提供。本职业提案的教育和研究部分建立在俄克拉荷马州立大学支持的先前和正在进行的工作以及现有设备的基础上。