CPS: Small: A Convex Framework for Control of Interconnected Systems over Delayed Networks

CPS：小型：延迟网络上互连系统控制的凸框架

基本信息

批准号：
1739990
负责人：
Matthew Peet
金额：
$ 30.47万
依托单位：
Arizona State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-15 至 2021-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1739990&HistoricalAwards=false
关键词：
CPS Small Convex Framework Control

项目摘要

Recent years have seen an explosion in the use of cellular and wifi networks to deploy fleets of semi-autonomous physical systems, including unmanned aerial vehicles (UAVs), self-driving vehicles, and weather stations to perform tasks such as package delivery, crop harvesting, and weather prediction. The use of cellular and wifi networks has dramatically decreased the cost, energy, and maintenance associated with these forms of embedded technology, but has also added new challenges in the form of delay, packet drops, and loss of signal. Because of these new challenges, and because of our limited understanding of how unreliable communication affects performance, the current protocols for regulating physical systems over wireless networks are slow, inefficient, and potentially unstable. In this project we develop a new computational framework for designing provably fast, efficient and safe protocols for the control of fleets of semi-autonomous physical systems. The systems considered in this project are dynamic, defined by coupled ordinary differential equations, and connected by feedback to a controller, with a feedback interconnection which has multiple static delays, multiple time-varying delays, or is sampled at discrete times. For these systems, we would like to design optimal and robust feedback controllers assuming a limited number of sensor measurements are available. Specifically, we seek to design a class of algorithms which are computationally efficient, which scale to large numbers of subsystems, and which, given models of the dynamics, communication links, and uncertainty, will return a controller which is provably stable, robust to model uncertainty, and provably optimal in the relevant metric of performance. To accomplish this task, we leverage a new duality result which allows the problem of controller synthesis for infinite-dimensional systems to be convexified. This result allows the problem of optimal and robust dynamic output-feedback controller synthesis to be reformulated as feasibility of a set of convex linear operator inequalities. We then use semidefinite programming to parametrize the set of feasible operators and thereby test feasibility of the inequalities with little to no conservatism. In a similar manner, estimator design and optimal controller synthesis are recast as semidefinite programming problems and used to solve the problems of sampled-data and systems with input delay. The algorithms will be scalable to at least 20 states and the controllers will be field-tested on a fleet of wheeled robotic vehicles.

近年来，使用细胞和WiFi网络来部署半自治物理系统的舰队，包括无人驾驶飞机（UAV），自动驾驶汽车和气象站，以执行诸如包装交付，农作物收获和天气预报等任务。细胞和WiFi网络的使用大大降低了与这些形式的嵌入式技术相关的成本，能量和维护，但也以延迟，数据包下降和信号损失的形式增加了新的挑战。由于这些新挑战，并且由于我们对不可靠的沟通如何影响性能的有限理解，因此在无线网络上调节物理系统的当前协议是缓慢，效率低下且潜在不稳定的。在这个项目中，我们开发了一个新的计算框架，用于设计可证明快速，高效和安全的协议，以控制半自治物理系统的机队。该项目中考虑的系统是动态的，由耦合的普通微分方程定义，并通过反馈连接到控制器，其反馈互连具有多个静态延迟，多个时间变化的延迟或在离散时间进行采样。对于这些系统，我们希望设计最佳和鲁棒的反馈控制器，假设有数量有限的传感器测量值。具体而言，我们试图设计一类计算上有效的算法，这些算法会扩展到大量子系统，并且给定动力学，通信链接和不确定性的模型，它将返回一个控制器，该控制器可证明是稳定的，可靠的，可模拟不确定性，并且在相关性能的相关指标中是最佳的。为了完成这项任务，我们利用了新的二元性结果，该结果允许对无限维系统的控制器合成问题进行启用。该结果允许将最佳和鲁棒的动态输出反馈控制器合成问题重新构成，以作为一组凸线性操作员不等式的可行性。然后，我们使用半决赛编程来参数可行的操作员集，从而测试几乎没有保守主义的不平等现象的可行性。以类似的方式，估计器设计和最佳控制器合成是作为半决赛编程问题重铸，并用于解决以输入延迟的方式解决采样数据和系统的问题。该算法将至少可扩展到20个州，并且控制器将在轮式机器人车辆的车队上进行现场测试。