Compute-Aware Control Systems: Coordinated Control of Physical Systems and Computer Processes

现代产品的核心越来越多地包括嵌入式处理器，这些处理器控制着物理系统，如灯光、机动机构和通信。这些发展得益于嵌入式处理器技术的日益成熟，该技术可以在运行时重新配置计算系统，以提高性能或功耗。然而，目前的做法是将处理器的控制器与物理系统控制器分开设计，忽略了协同的机会。本研究的重点是开发协调处理器和物理系统控制器设计的方法，以提供更大的设计灵活性。具体来说，这种协调将使物理系统控制算法具有计算意识，即适应计算系统的波动需求和限制。类似地，将设计一个计算机过程控制器来动态管理计算过程的功率和性能，以响应物理系统控制器不断变化的需求。这项工作的影响是用于控制应用的嵌入式处理器可以缩小，重量更轻，功耗更低，同时仍然保持稳定性和良好的性能。预计最有利的应用是自供电系统，如移动机器人和空中机器人，特别是那些尺寸和重量很重要的应用。本研究的目的是发展物理系统控制器和计算系统控制器的协调控制方法。本研究将理论框架与软件架构相结合，以设计和分析由物理系统控制器和计算系统控制器集成而产生的随机混合系统。研究人员将开发稳定性分析方法和新的设计方法，将随时算法的适用性扩展到更大类别的控制律和更大类别的物理系统。为计算系统开发的预测控制方法将使系统对计算机处理器的波动需求具有高响应性。要使用的计算机科学方法包括软实时计算、可重用软件框架以及软件验证和验证方法的概念。要开发的体系结构有三个基本组成部分：计算感知物理系统控制器：将标准控制器重新制定为随时算法，可以随时停止或重新配置，因为计算机资源的突然限制；计算机功率与性能控制器：用于计算机进程的控制器，可适应物理系统控制器不断变化的要求；高级协调控制器：管理计算机系统和物理系统控制器的功率和性能要求之间的权衡的算法。所有开发的方法将通过蒙特卡罗模拟和实验进行验证。

Increasingly, the heart of modern products includes embedded processors that control physical systems such as lights, motorized mechanisms, and communications. These developments are enabled by the increasing sophistication of embedded processor technology that can reconfigure the computing system while it is running in order to improve performance or power usage. However, current practice is to design the controller of the processor separately from the physical system controller, overlooking the opportunity for synergy. The focus of this research is to develop methods to coordinate the design of the processor and physical-system controllers in order to give more design flexibility. Specifically, this coordination will make the physical system control algorithms compute-aware, that is, adaptive to the fluctuating demands and limitations of the computing systems. Similarly, a computer process controller will be designed that dynamically manages the power and performance of the computing processes in response to the changing demands of the physical system controller. The impact of this work is that embedded processors used for controls applications can be downsized, made lighter in weight and lower power, while still maintaining stability and good performance. The applications that are expected to have the most benefit are self-powered systems such as mobile robots and aerial robots, especially ones where size and weight are important.The objective of this research is to develop coordinated control methods for the physical system controller and the computing system controller. The research will combine a theoretical framework with a software architecture in order to design and analyze the stochastic hybrid system that arises from integrating the physical system controller and the computing system controllers. The researchers will develop stability analysis methods and new design methods that will expand the applicability of anytime algorithms to larger classes of control laws and larger classes of physical systems. The predictive control methods to be developed for computing systems will make the system highly responsive to the fluctuating demands on the computer processor. The computer science approaches to be used include the concepts of soft-real-time computing, reusable software frameworks, and software verification and validation methods. The architecture to be developed has three basic components: Compute-Aware Physical System Controllers: standard controllers reformulated into Anytime Algorithms, which can be stopped or reconfigured anytime due to sudden limitations in the computer resources; Computer Power and Performance Controller: a controller for computer processes that adapts to changing requirements of the physical system controller; and a High-Level Coordination Controller: algorithms that manage the trade-off between the power and performance requirements of the computer system and of the physical system controller. All of the developed methods will be validated through Monte Carlo simulations and experiments.