CPS: Small: Scalable and safe control synthesis for systems with symmetries

在物联网、交通运输和电力系统等许多应用中，能够在保持安全保证的同时适应环境的复杂工程系统至关重要。该项目的主要目标是开发一种可扩展的设计方法来控制非常大的系统集合，以实现共同的目标，尽管网络和物理限制。作为一个应用，将考虑电力负荷控制问题，其目标是在不给电力消费者带来不便的同时，在尊重配电网物理限制的情况下，协调空调、冰箱等成千上万个小型电力负荷的用电量，以帮助电网平衡供需。研究结果将支持更多的风能和太阳能的整合，改善电网的环境和健康影响。教育和推广活动将涉及K-12，本科生和研究生以及当地电力公司的利益相关者。所考虑的问题的关键特征是大量的动态几乎解耦的系统。每个系统都有自己的局部需求和约束，并且它们通过有关其集体行为的需求耦合在一起。将开发一种双层控制体系结构，该体系结构可以处理软性能要求并允许上层的适应性，并保证在下层满足硬安全要求。较低层次将利用系统的结构特性对称性和要求，特别是排列不变性，以实现高度可扩展的合成方法，以确保安全性。上层将利用适应/学习来提高系统性能，当控制输入出于安全目的被覆盖时。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Complex engineered systems that can adapt to their environments while maintaining safety guarantees are crucial in many applications including Internet-of-Things, transportation, and electric power systems. The primary objective of this project is to develop a scalable design methodology to control very large collections of systems to achieve common objectives despite cyber and physical constraints. As an application, the electric load control problem, in which the goal is to coordinate the power consumption of thousands of small electric loads like air conditioners and refrigerators to help the grid balance supply and demand without inconveniencing electricity consumers and while respecting the physical limitations of the power distribution network, will be considered. The research results will support the integration of more wind and solar power, improving the grid's environmental and health impacts. Education and outreach activities will involve K-12, undergraduate, and graduate students along with stakeholders from local power companies.The key characteristics of the problems considered are a large number of dynamically almost decoupled systems. Each system has their local requirements and constraints and they are coupled through requirements about their collective behavior. A bi-level control architecture will be developed that can handle soft performance requirements and allow adaptability at the upper-level, and that guarantees the satisfaction of hard safety requirements at the lower-level. The lower-level will exploit structural properties symmetries of the systems and requirements, in particular, permutation invariance, to enable highly scalable synthesis methods to ensure safety. The upper-level will leverage adaptation/learning to improve system performance when control inputs are overridden for the purpose of safety.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.