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

使用鲁棒模型预测控制解决具有共享资源的复杂控制系统的争用

• 批准号: 2218517
• 负责人: Ningshi Yao
• 金额: $ 32.97万
• 依托单位: George Mason University
• 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: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2218517&HistoricalAwards=false
• 关键词: Resolving; Contentions; Complex; Control; Systems

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.

随着现代工业和智慧城市中系统和数据的大规模，云计算、通信网络和电网等共享资源被广泛使用，以降低系统成本并增加可维护性。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。冲突可能导致信息丢失、时间延迟甚至危及生命的安全问题。因此，如何调度系统以解决竞争是一个通用的问题，控制的复杂系统，耦合或连接通过共享资源。为了帮助解决这个问题，该项目将开发变革性控制技术，以协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与复杂的数学相结合，旨在产生具有严格性能的实用方法。一旦验证并过渡到实际应用中，该项目开发的策略将有可能减少交通和运输系统的拥堵和污染，造福人类社会和自然环境。通过一系列紧密结合的研究、教育和外展活动，该项目还将有助于扩大STEM研究中代表性不足的群体的参与。该项目解决了三个主要问题，以推进与共享资源的连接系统相关的控制理论：如何开发一种通用方法，可以在统一的理论框架中共同设计调度和控制;如何有效地在线计算实时系统的协同设计解决方案;以及如何解决协同设计问题中的现实不确定性。为了回答这些问题，本计画将发展一个强健的竞争解决模型预测控制（MPC）方法作为统一的理论架构。分析时间模型将建立在并行机，流水车间，车间调度的背景下，不同类型的实时控制系统与共享资源的模型。然后，基于定时模型，设计一个事件触发的MPC，以实现足够快的实时计算。为了补偿不确定性，该项目还将为竞争解决MPC开发基于前向不变集的鲁棒设计，以保证在系统干扰和扰动事件时序下的性能。将通过逼真的模拟软件包和现场实验来验证所提出的方法，以测试现实的不确定性和变化下的设计。总体框架将是一般的各种应用，包括更高的维度系统，是令人信服的持续利益engineering.This奖项反映了NSF的法定使命，并已被认为是值得的支持，通过评估使用基金会的智力价值和更广泛的影响审查标准。