Finite-time Containment Control for Lagrangian Networks

目的：研究拉格朗日网络的分布式有限时间包容控制问题。尽管事实上，包含控制，网络系统的有限时间控制和拉格朗日网络控制的每一个主题是至关重要的网络多智能体系统，有几个现有的结果对每个主题更不用说三个组合由于许多固有的挑战。本研究解决了在一个统一的framework.Intellectual Merit的三个主题的组合：分布式算法将被设计为保证有限时间遏制控制拉格朗日网络与固定的领导者，动态的领导者，和群集行为，并将在异构机器人网络实验验证。该研究的新奇在于范式的变化i）从多智能体系统中主要研究的无领导者或单一领导者行为到更现实但复杂的多领导者多跟随者行为，涉及多个异构智能体团队之间的多层协作，ii）从分布式算法，只能保证渐近或最多指数收敛在无限时间占主导地位的探索，在多-从多智能体系统中主要采用的简化/理想化的线性点模型到代表包括自主车辆和机器人操纵器在内的一大类机械系统的更现实和普遍的非线性拉格朗日模型。更广泛的影响：该研究对许多民用，国土安全和军事应用以及与网络系统相关的其他领域（包括生物学，社会学和物理学）产生了影响。将开发一个关于自主系统的顶点课程，重点是动手实验室和校园范围的机器人竞赛。将通过参与工程州犹他州的全州工程项目，向高中生开展外联活动。将通过出版物、辅导讲习班、暑期学校和专门网站广泛传播研究成果。

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.