Finite-time Containment Control for Lagrangian Networks

拉格朗日网络的有限时间遏制控制

• 批准号: 1213295
• 负责人: Wei Ren
• 金额: $ 27.33万
• 依托单位: University of California-Riverside
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-11-04 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1213295&HistoricalAwards=false
• 关键词: Finite; time; Containment; Control; Lagrangian

Objective:The objective of this research is to address the problem of distributed finite-time containment control for Lagrangian networks. Despite the fact that each topic of containment control, finite-time control of networked systems, and control of Lagrangian networks is crucial for networked multi-agent systems, there are few existing results on each topic not to mention a combination of the three due to numerous inherent challenges. This research addresses a combination of the three topics in a unified framework.Intellectual Merit:Distributed algorithms will be designed to guarantee finite-time containment control for Lagrangian networks with stationary leaders, dynamic leaders, and swarming behavior and will be experimentally validated on heterogeneous robotic networks. The novelty of the research lies in the paradigm changes i) from leaderless or single leader behaviors dominantly studied in multi-agent systems to more realistic but complicated multi-leader multi-follower behaviors involving multi-layer collaboration between multiple heterogeneous teams of agents, ii) from distributed algorithms that can only guarantee asymptotic or at most exponential convergence in infinite time dominantly explored in multi-agent systems to distributed algorithms that are guaranteed to converge in finite time to meet the needs of many time-critical missions, and iii) from simplified/idealized linear point models dominantly adopted in multi-agent systems to more realistic and prevalent nonlinear Lagrangian models that represent a large class of mechanical systems including autonomous vehicles and robotic manipulators.Broader Impacts: The research has impact on numerous civilian, homeland security, and military applications and on other fields related to networked systems including biology, sociology, and physics. A capstone course on autonomous systems will be developed with emphasis on hands-on labs and campus-wide robotics competitions. Outreach activities to high school students will be pursued through involvement in a state-wide engineering program in Utah, Engineering State. Broad dissemination of the research results will be accomplished through publications, tutorial workshops, a summer school, and a dedicated website.

目的：这项研究的目的是解决拉格朗日网络分布式有限时间控制控制的问题。尽管每个主题控制控制，对网络系统的有限时间控制以及对拉格朗日网络的控制对于网络多代理系统至关重要，但由于许多固有的挑战，每个主题上的现有结果几乎没有现有的结果。这项研究介绍了统一框架中三个主题的组合。智能优点：分布式算法将旨在保证具有固定领导者，动态领导者和群体行为的拉格朗日网络的有限时间控制控制，并将在异构性机器人网络上进行实验验证。这项研究的新颖性在于范式的变化i）从无领导者或单一领导行为中主要研究到多代理系统中的研究到更现实但复杂的多领导者多游行者行为，涉及多层协作，涉及多个异构团队之间的多层协作，ii仅能保证分布式算法的构造，以构成等级的构成，以构成等准的构成，以构成相正的构成。多机构系统到分布的算法，这些算法可以保证在有限的时间内融合以满足许多时间至关时间任务的需求，iii）从简化/理想化的线性点模型中，在多机构系统中主要采用了在多代理系统中的主要采用，到更现实和普遍的非线性lagrangian lagrangian模型，这些模型代表了包括自动企业的大型机械型制度。安全，军事应用以及与网络系统有关的其他领域，包括生物学，社会学和物理学。将开发有关自主系统的顶峰课程，重点是动手实验室和校园范围内的机器人竞赛。通过参与犹他州工程州的一项州范围的工程计划，将向高中生提供外展活动。研究结果的广泛传播将通过出版物，教程研讨会，暑期学校和专门的网站来完成。