Resolving Contentions for Complex Control Systems with Shared Resources using Robust Model Predictive Control

随着现代工业和智慧城市系统和数据的大型化，云计算、通信网络、电网等共享资源被广泛使用，以降低系统成本，增加可维护性。当多个系统需要同时访问共享资源并且总需求超过总供应时，就会发生争用。争执可能导致信息丢失、时间延误甚至危及生命的安全问题。因此，对于通过共享资源耦合或连接的复杂系统的控制而言，如何调度系统以解决争用是一个普遍问题。为了帮助解决这个问题，该项目将开发变革性控制技术，以共同设计资源受限控制系统的调度和控制策略。该项目将富有洞察力的工程学与复杂的数学相结合，目标是产生具有严格性能的实用方法。一旦得到验证并转化为实际应用，该项目开发的战略将有可能减少交通运输系统的拥堵和污染，并造福于人类社会和自然环境。通过一系列高度集成的研究、教育和推广活动，该项目还将帮助代表不足的群体更广泛地参与STEM研究。该项目解决了三个主要问题，以促进关于具有共享资源的互联系统的控制理论：如何开发一种通用方法，能够在统一的理论框架中共同设计调度和控制；如何在线高效地计算实时系统的共同设计解决方案；以及如何解决共同设计问题中的现实世界不确定性。为了回答这些问题，本项目将开发一种鲁棒的冲突解决模型预测控制(MPC)方法作为统一的理论框架。将在并行机、流水作业车间和作业车间调度的背景下建立分析时间模型，以对具有共享资源的不同类型的实时控制系统进行建模。然后在时序模型的基础上，设计了一种事件触发的MPC，以实现足够快的实时计算。为了补偿不确定性，该项目还将开发基于前向不变集的竞争解决预测控制的稳健设计，以保证在系统扰动和扰动事件定时下的性能。所提出的方法将通过现实的仿真软件包和现场实验来验证，以测试在现实的不确定性和变化下的设计。总体框架将适用于各种应用，包括在工程上具有强烈持续兴趣的高维系统。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

With the large scale of systems and data in modern industries and smart cities, shared resources, such as cloud computing, communication network, and power grid, are widely used to reduce system cost and increase maintainability. When multiple systems need access to shared resources at the same time and the total demands exceed the total supply, a contention occurs. Contentions can cause loss of information, time delay or even life-threatening safety issues. Therefore, how to schedule systems to resolve contentions is a generic problem for the control of complex systems that are coupled or connected through shared resources. To help address this problem, this project will develop transformative control techniques to co-design scheduling and control strategies for resource constrained control systems. The project combines insightful engineering with sophisticated mathematics, towards the goal of producing practically useful approaches that have rigorous performance. Once validated and transitioned to actual applications, the strategies developed by this project will have the potential to reduce congestion and pollution from traffic and transportation systems and benefit both human society and natural environment. Through a series of strongly integrated research, educational, and outreach activities, the project will also help broaden participation of underrepresented groups in STEM research.This project addresses three main questions to advance the control theory regarding to connected systems with shared resources: how to develop a general method which can co-design the scheduling and control in a unified theoretical framework; how to compute a co-design solution efficiently online for real-time systems; and how to address real-world uncertainties in the co-design problem. To answer these questions, this project will develop a robust contention-resolving model predictive control (or MPC) method as the unified theoretical framework. Analytical timing models will be established in the context of parallel machines, flow shop, and job shop scheduling to model different types of real-time control systems with shared resources. Then based on the timing models, an event-triggered MPC will be designed to achieve fast enough computation in real-time. To compensate uncertainties, the project will also develop a robust design based on forward invariant set for contention-resolving MPC to guarantee performance under system disturbances and perturbed event timing. The proposed approaches will be validated through realistic simulation software packages and field experiments to test the designs under realistic uncertainties and variations. The overall framework will be general for various applications including higher dimensional systems that are of compelling ongoing interest in engineering.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.