Analysis and Design of Robust Control Schemes for Networks of Non-Uniform Infrastructure Responding to Aggregated User Demand

随着传感和通信技术变得更快、更小、更便宜，它们与我们世界中的公共基础设施和公用事业越来越紧密地结合在一起。这项新技术可广泛用于公众，可用于创建更先进的系统，其中智能设备通过实时通信网络与用户和运营商连接。现代的例子包括交通系统、电网、智能建筑和自动化工厂环境。用户和运营商之间的协调可以大大提高这些网络基础设施系统的效率，同时减少拥塞和高需求问题。该奖项支持基础研究，为自动控制算法的开发提供所需的知识和技术，这些算法可以在保证性能的情况下实现这些目标。 多个用户和操作员的协调是非常具有挑战性的，因为交互仅在本地发生，用户/操作员的需求可能会由于不可预测的事件、高需求期间的服务的潜在限制以及智能设备操作的不可靠性而迅速改变。这项研究将弥合现有的理论工具，并开发新的，可用于指导新的鲁棒算法的设计。 因此，这项研究的成果将有利于美国的经济和社会。这项研究涉及多个学科，包括控制理论，分布式计算，优化和机器人。多学科的方法将有助于扩大参与研究的代表性不足的群体和积极的影响engineering education.This项目的研究目标是分布式协调和重新路由算法的控制网络系统的设计受到各种各样的情况下的约束。该研究计划是阐明沿着以下推力：（一）基于聚合的强大的需求响应算法的负载转移的设计：虽然聚合可以帮助实现负载转移的目标，关键是要了解其鲁棒性的噪声，时变相互作用和延迟。 (ii)分布式负载重平衡和重路由算法的设计：异构约束会对分布式算法行为产生巨大影响，打破自然的多代理交互流，导致拥塞。我们的目标是研究如何重新分配可以帮助缓解拥堵。(iii)需求响应算法与分布式路由和平衡算法的集成。将使用非线性稳定性工具来分析算法的鲁棒性，方法是弥合高度李雅普诺夫函数的光滑理论、集值映射理论和收缩分析之间的现有差距。

As sensing and communication technologies become faster, smaller and cheaper, they become ever more integrated with common infrastructure and utilities in our world. Widely available to the public, the new technology can be leveraged to create more advanced systems where smart devices are linked with users and operators by real-time communication networks. Modern examples include traffic systems, the power grid, smart buildings, and automated factory environments. The coordination between users and operators can dramatically expand the efficiency of these networked infrastructure systems, while reducing problems of congestion and high demand. This award supports fundamental research to provide needed knowledge and techniques for the development of automatic control algorithms that can meet these goals with guaranteed performance. The coordination of multiple users and operators is very challenging as interactions occur only locally, user/operator needs can quickly change due to unpredicted events, the potential limitations of service over periods of high demand, and the unreliability of the smart device operation. This research will bridge existing theoretical tools and develop new ones that can be used to guide the design of novel robust algorithms. Therefore, results from this research will benefit the U.S. economy and society. This research involves several disciplines including control theory, distributed computation, optimization, and robotics. The multi-disciplinary approach will help broaden participation of underrepresented groups in research and positively impact engineering education.This project's research objectives are the design of distributed coordination and re-routing algorithms for the control networked systems subject to constraints in a wide variety of scenarios. The research plan is articulated along the following thrusts: (i) The design of aggregation-based robust demand-response algorithms for load shifting: While aggregation can help achieve load-shifting objectives, it is key to understand its robustness properties with respect to noise, time-varying interactions, and delays. (ii) The design of distributed load re-balancing and re-routing algorithms: Heterogeneous constraints can have a dramatic impact on distributed algorithm behavior, breaking the natural multi-agent interaction flow and leading to congestion. We aim to study how re-distribution can help alleviate congestion. (iii) The integration of demand-response algorithms with distributed routing and balancing algorithms. Nonlinear stability tools will be used to analyze the robustness of the algorithms by bridging existing gaps between the smooth theory of height Lyapunov functions, set-valued map theory, and contractive analysis.