EAGER: Extensible Linear Distributed Controllers for Large Multi-Input-Multi-Output Systems, with Applications to Control of Networked Printers

这一早期概念探索性研究拨款研究项目的目标是复杂的多输入多输出系统的控制设计，该系统具有非常大的状态空间维度，部分未知的状态空间模型，其中模型的未知部分虽然在实践中可以识别，但需要估计一个耗时或昂贵的过程。这类工厂涵盖了大量的工业和计算机物理系统，从化学过程到制造系统再到高质量的多机静电复制系统，这些都构成了我们工作的主要驱动应用和试验台。对于这样的系统，精确的模型辨识是可能的，但成本很高，控制工程师通常面临辨识和闭环系统性能之间的权衡。找到合适的``关键参数？要确定某一特定的监管任务，并确定“好的”辨识/性能权衡，传统上大多是经验和经验法则的问题，通常占据了实践控制工程师的相当大一部分时间。这个项目提出了一种新的开发实用技术的方法，可以帮助实践者探索辨识/控制性能的权衡。其关键思想是建立在信号处理领域的新颖和快速的“压缩传感”算法的基础上，并将它们与更传统的控制设计思想相结合。这项研究将与位于纽约韦伯斯特的施乐公司S研究中心的科学家密切合作进行，这将确保所开发算法的相关性和实用适用性，并提供对实际静电打印试验台的访问。这一合作还将积极吸引一名研究生。我们期望本研究所产生的工具能广泛应用于工业控制设计领域。将通过在主要控制会议上组织辅导讲习班和初步开发开放源码软件工具箱来促进它们的传播。

The objective of this EArly-concept Grants for Exploratory Research (EAGER)research project is the control design for complex multi-input multi-output systems with very large state-space dimension, partially unknown state-space models, and in which the unknown part of the model, although identifiable in practice, requires a time-consuming or costly process to be estimated. This class of plants covers a large number of industrial and cyberphysical systems, from chemical processes to manufacturing systems to high-quality multi- machine xerographic reproduction systems, which constitute the main driving application and testbed for our work. For such systems in which precise model identification is possible but costly, the control engineer typically faces a trade-off between identification and closed-loop performance. Finding the appropriate ``critical parameters? to be identified for a particular regulation task and determining a ``good" identification/performance trade-off has traditionally been mostly a matter of experience and rules of thumb, and often occupies a significant portion of the practicing control engineer's time. This project proposes a new approach for developing practical techniques that can help the practitioner explore the identification/control performance trade-off. The key idea is to build on novel and fast ``compressed sensing" algorithms from the field of signal processing, and combine them with more traditional control design ideas. This research will be conducted in close collaboration with scientists at Xerox Corporation?s Research Center in Webster (NY, which will ensure the relevance and practical applicability of the developed algorithms, and provide access to an actual xerographic printing testbed. This collaboration will also actively engage a graduate student. We expect the tools resulting from this research to be widely applicable in industrial control design contexts. Their dissemination will be facilitated by the organization of tutorial workshops at leading control conferences, and the initial development of an open-source software toolbox.