Model Predictive Control with Discrete/Continuous Decisions: Theory, Computation, and Application

1603768 PI：罗林斯标题：离散/连续决策的模型预测控制：理论、计算和应用需要在线离散操作决策的系统，在控制环境中也称为执行器，无处不在。然而，在与过程控制相关的反馈控制理论的历史发展中，离散决策总是从在线控制问题中移除，并在自动化系统中的不同层面上进行考虑，通常使用启发式规则，例如按预先指定的顺序循环访问一些炉组或冷水机组。因此，在过程控制应用中，对这些离散决策的优化基本上没有实现，而对连续决策(阀门位置、施加电压、扭矩等)的优化。已经达到很高的水平，正如模型预测控制(MPC)在流程工业中的广泛使用所表明的那样。本研究项目的目标是实现对既有离散决策变量又有连续决策变量的过程的优化和反馈控制。PI建议开发新的理论和计算软件来解决这类问题。这项研究将与工业合作伙伴江森自控密切合作进行，研究成果将在涉及商业建筑供暖、通风和空调(HVAC)系统控制的应用程序中进行测试。建筑物中的能源消耗占美国能源消耗和碳排放的很大一部分。建议的新理论既包括标称的闭环系统稳定性，也包括对模型错误和干扰的内在稳健性，并要求通过连续决策(阀门位置、施加的电压、扭矩等)来扩展标准预测控制。对于既有连续变量又有离散变量的MPC(冷冻机、加热器、泵的开/关开关；在周期性、循环运行期间使用哪种设备等)。该项目旨在开发：(I)离散/连续执行器预测控制的新理论，(Ii)解决离散执行器预测控制问题的新的免费源码软件，以及(Iii)将大规模、复杂的建筑暖通空调控制问题分解为易于处理的子问题的方法。使能计算软件将以自由源码语言CasADi提供给所有研究人员，CasADi已成为解决大型、复杂和结构化最优控制问题的主要语言。将离散决策变量添加到CasADi中将为从业者提供一种工具，以在广泛的工业应用中实施这项研究的结果。PI计划培养一名研究生，并开发控制系统设计方面的新教材。

1603768 PI: RawlingsTitle: Model Predictive Control with Discrete/Continuous Decisions: Theory, Computation, and ApplicationSystems requiring online discrete operating decisions, also known as actuators in the control context, are ubiquitous. In the historical development of feedback control theory relevant to process control, however, the discrete decisions were always removed from the online control problem and considered at a different level in the automation system, often using heuristic rules, such as cycling through some bank of furnaces or chillers in a pre-specified order. As a result, optimization of these discrete decisions has seen essentially no implementation in process control applications, while optimization of the continuous decisions (valve positions, applied voltages, torques, etc.) has reached a high level, as demonstrated by the widespread use of model predictive control (MPC) in the process industries. The goal of this research project is to enable optimization and feedback control of processes that have discrete as well as continuous decision variables. The PI proposes to develop both new theory and computational software to address this class of problems. The research will be conducted in close collaboration with an industrial partner, Johnson Controls, and the research results will be tested in applications involving control of heating, ventilation, and air conditioning (HVAC) systems in commercial buildings. Energy use in buildings is responsible for a significant fraction of energy consumption and carbon emissions in the US.The proposed new theory encompasses both nominal closed-loop stability and inherent robustness to model errors and disturbances, and requires extension of standard MPC with continuous decisions (valve positions, applied voltages, torques, etc.) to MPC with both continuous and discrete variables (on/off switches for chillers, heaters, pumps; which equipment to use when during a periodic, cyclic operation, etc.). The proposed project aims to develop: (i) new theory for MPC with discrete/continuous actuators, (ii) new free-source software to solve the MPC control problem with discrete actuators, and (iii) an approach for decomposing the large-scale, complex building HVAC control problem into tractable sub-problems. The enabling computational software will be made available to all researchers in the free-source language CasADi, which has become the leading language for solving large, complex, and structured optimal control problems. Adding discrete decision variables to CasADi will provide practitioners with a tool to implement the results of this research in a broad range of industrial applications. The PI plans to train a graduate student and develop new educational materials on control system design.