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中系统和数据的规模化，云计算、通信网络、电网等共享资源被广泛应用，以降低系统成本，提高可维护性。当多个系统同时需要访问共享资源，并且总需求超过总供应时，就会发生争用。争用可能导致信息丢失、时间延迟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，如何调度系统来解决争用问题是一个普遍的问题。为了帮助解决这个问题，这个项目将开发变革性的控制技术，为资源受限的控制系统共同设计调度和控制策略。该项目将富有洞察力的工程与复杂的数学相结合，以产生具有严格性能的实用方法为目标。一旦得到验证并转化为实际应用，本项目制定的策略将有可能减少交通和运输系统的拥堵和污染，并造福人类社会和自然环境。通过一系列强有力的综合研究、教育和推广活动，该项目还将帮助扩大代表性不足的群体参与STEM研究。本课题主要解决三个问题，以推进资源共享互联系统的控制理论：如何在统一的理论框架下开发一种通用的调度与控制协同设计方法；如何在线高效地计算实时系统的协同设计方案以及如何解决协同设计问题中现实世界的不确定性。为了回答这些问题，本项目将开发一个鲁棒的争议解决模型预测控制（或MPC）方法作为统一的理论框架。在并行机器、流水车间和作业车间调度的背景下，建立分析时序模型，对具有共享资源的不同类型的实时控制系统进行建模。在此基础上，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，该项目还将开发一种基于前向不变集的鲁棒设计，用于争用解决MPC，以保证在系统干扰和扰动事件定时下的性能。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，包括在工程中引人注目的持续兴趣的高维系统。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.