Development of Robust Tools for Simultaneous Design and Control and Multiscale Modeling and Control

本研究的目的是设计新的数字工具的集成设计和控制的动态系统和可控性的系统描述的多尺度建模方法。 设计和控制的一体化：本研究将开发一种新的优化设计和控制方法，该方法受最坏情况发生概率的影响，即，由于扰动的变化而导致的输出中的最大偏差。由此产生的方法将影响工程实践的不同领域，因为它将被用作一个实用和有效的工具，以优化设计和控制大规模的工业应用。例如，这种方法将应用于加拿大自然资源部下属的CanmetEnergy运营的二氧化碳捕获试验工厂。因此，这项研究有可能增加工厂的能力，通过重新设计这个试点工厂，或提出一个新的设计，可用作基础，设计商业规模的二氧化碳捕集厂，以捕获二氧化碳。 多尺度建模和控制：将设计新的鲁棒灵敏度工具，使多尺度建模为基础的系统的控制。多尺度模型是一组相互关联的模型，描述系统在不同时间和长度尺度上的行为。所提出的控制策略将占两个，所产生的不确定性的精细尺度模型参数和当前的能力的传感器用于测量发生在精细尺度的事件在一个过程中。因此，由此产生的控制技术将提供一个更现实的方法来控制基于多尺度建模的系统，这通常出现在半导体工业中的应用。例如，目前正在设计化学气相沉积（CVD）系统的一家当地公司有兴趣对这种基于多尺度建模的过程实施实时控制。因此，这项研究将推进加拿大在这一新兴领域的知识，因为在这项研究中提出的控制策略将有可能被实施的在线控制薄膜生产，如CVD工艺的相关工业应用。

The present research aims to design new numerical tools for the integration of design and control of dynamic systems and for the controllability of systems described with a multiscale modeling approach. Integration of design and control: This research will develop a new optimal design and control methodology that is subject to a probability of occurrence of the worst-case scenario, i.e., the largest deviation in the outputs due to changes in the disturbances. The resulting methodology will impact on different areas of engineering practice since it will be used as a practical and efficient tool to optimally design and control large-scale industrial applications. For example, this method will be applied to a CO2 capture pilot plant operated by CanmetEnergy, a division of Natural Resources Canada. Thus, this research has the potential to increase the plant's capacity to capture CO2 by redesigning this pilot plant or to propose a new design that can be used as a basis to design commercial-scale CO2 capture plants. Multiscale modeling and control: New robust sensitivity tools that enable the control of multiscale modeling-based systems will be designed. A multiscale model is a set of interconnected models that describe the behaviour of systems at different time and length scales. The proposed control strategies will account for both, the uncertainty arising from the fine scale model parameters and the current capabilities of the sensors used to measure the events occurring at the fine scales in a process. Thus, the resulting control technologies will provide with a more realistic approach to control multiscale modeling-based systems, which usually emerge in applications in the semiconductor industry. For example, a local company that is currently designing a Chemical Vapour Deposition (CVD) system is interested to implement real-time control for this multiscale modeling-based process. Thus, this research will advance Canada's knowledge on this emerging field because the control strategies proposed in this research will have the potential to be implemented for the on-line control of relevant industrial applications for thin films production such as CVD processes.