Distributed Time-varying Coordination of Uncertain Nonlinear Multi-agent Systems: A Unified Model Reference Scheme

不确定非线性多智能体系统的分布式时变协调：统一模型参考方案

• 批准号: 2129949
• 负责人: Wei Ren
• 金额: $ 37.5万
• 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: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2129949&HistoricalAwards=false
• 关键词: Distributed; Time; varying; Coordination; Uncertain

Distributed coordination of multi-agent systems has numerous applications. Existing research on distributed multi-agent coordination is often limited to static problems, while time-varying problems can respond to moving objects of interest and real-time changes in the environment/missions (for example, coordinated exploration, cooperative monitoring, cooperative transport, region-following formation tracking, and multi-robot multitarget navigation) but are more challenging. In reality, multi-agent systems often exhibit nonlinearity and uncertainty but corresponding results are limited. Addressing the two aspects (distributed time-varying coordination and uncertain nonlinear agent dynamics) simultaneously will substantially enhance the existing functionality of multi-agent systems. Unfortunately, the interwoven challenges caused by the two aspects are often intractable, not to mention further complexity due to switching graphs and partial measurements. A systematic approach to tackle the two aspects simultaneously is lacking. This project aims at deriving a novel model reference coordination scheme to bridge the gap between distributed coordination of linear systems and tracking control of a single uncertain nonlinear system. Education and outreach activities will broaden participation of underrepresented groups in research.The objective of this project is to derive a novel unified model reference coordination scheme combined with new inverse backstepping thinking in design to systematically address distributed time-varying coordination of uncertain nonlinear multi-agent systems. In the proposed scheme, each agent’s reference model is chosen as a linear system driven by distributed time-varying nonsmooth nonlinear coordination terms defined by physical states between neighbors (e.g., relative state/output measurements). Distributed time-varying coordination of uncertain nonlinear multi-agent systems is divided into three parts: i) coordination of the reference models themselves; ii) tracking of the state/output of each agent's reference model by with uncertain nonlinear dynamics; iii) study of mutual influence/feedback of the first two parts. The PI will explore the usage of the scheme to accommodate various uncertainties and dynamics and address distributed time-varying coordination with nonsmooth nonlinear algorithms accounting for unavailable information and heterogeneous uncertain systems of different types and orders. The proposed research will solve challenging open research problems and advance the state of the art in distributed multi-agent coordination.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

多智能体系统的分布式协调有许多应用。现有的分布式多智能体协调研究通常局限于静态问题，而时变问题可以响应感兴趣的移动对象和环境/任务的实时变化。例如，协调探索、合作监测、合作运输、区域跟踪编队跟踪和多机器人多目标导航），但在现实中，多智能体系统往往表现出非线性和不确定性，但解决这两个问题的相应结果是有限的。方面（分布式不幸的是，这两个方面造成的相互交织的挑战往往是棘手的，更不用说由于切换图和部分测量而导致的进一步复杂性。缺乏同时解决这两个方面的系统方法，该项目旨在推导一种新颖的模型参考协调方案，以弥合线性系统的分布式协调和单个不确定非线性系统的跟踪控制之间的差距。教育和推广活动将扩大参与范围。中代表性不足的群体该项目的目标是导出一种新颖的统一模型参考协调方案，在设计中结合新的逆反推思想，以任意解决不确定非线性多智能体系统的分布式时变协调。在该方案中，每个智能体的参考模型。被选为由邻居之间的物理状态定义的分布式时变非光滑非线性协调项驱动的线性系统（例如，相对状态/输出测量）不确定非线性多智能体系统的分布式时变协调被分为三个。部分：i）参考模型本身的协调；ii）通过不确定的非线性动力学跟踪每个代理参考模型的状态/输出；iii）研究前两部分的相互影响/反馈。该方案适应各种不确定性和动态性，并通过非光滑非线性算法解决分布式时变协调问题，解决不可用信息和不同类型和阶数的异构不确定系统的问题。所提出的研究将解决具有挑战性的开放研究问题，并推进最先进的技术。在分布式多主体协调。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Distributed Continuous-Time Resource Allocation Algorithm for Networked Double-Integrator Systems with Time-Varying Non-Identical Hessians and Resources

时变非同质Hessian和资源网络双积分系统的分布式连续时间资源分配算法

• DOI: 10.23919/acc55779.2023.10156380
• 发表时间: 2023-05-31
• 期刊: 2023 American Control Conference (ACC)
• 作者: Yong Ding;W. Ren;Ziyang Meng
• 通讯作者: Ziyang Meng

Distributed Time-Varying Quadratic Optimal Resource Allocation Subject to Nonidentical Time-Varying Hessians With Application to Multiquadrotor Hose Transportation

非同时变Hessian分布的时变二次最优资源分配及其在多四旋翼软管运输中的应用

• DOI: 10.1109/tsmc.2021.3137814
• 发表时间: 2022-10-01
• 期刊: IEEE Transactions on Systems, Man, and Cybernetics: Systems
• 作者: B. Wang;Shan Sun;W. Ren
• 通讯作者: W. Ren

A Distributed Time-Varying Optimization Algorithm For Networked Lagrangian Agents Generating Continuous Control Torques

网络拉格朗日智能体生成连续控制扭矩的分布式时变优化算法

• DOI: 10.23919/acc55779.2023.10156384
• 发表时间: 2023-05-31
• 期刊: 2023 American Control Conference (ACC)
• 作者: Yong Ding;H. Wang;Jie Mei;W. Ren
• 通讯作者: W. Ren

Stability of multi-dimensional switched systems with an application to open multi-agent systems

多维交换系统的稳定性及其开放多智能体系统的应用

• DOI: 10.1016/j.automatica.2022.110644
• 发表时间: 2022-12
• 期刊: Automatica
• 影响因子: 6.4
• 作者: Xue, Mengqi;Tang, Yang;Ren, Wei;Qian, Feng
• 通讯作者: Qian, Feng

Distributed Continuous-Time Algorithms for Time-Varying Constrained Convex Optimization

用于时变约束凸优化的分布式连续时间算法

• DOI: 10.1109/tac.2022.3198113
• 发表时间: 2023-07-01
• 期刊: IEEE Transactions on Automatic Control
• 影响因子: 6.8
• 作者: Shan Sun;J. Xu;W. Ren
• 通讯作者: W. Ren