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

在包括物联网、交通和电力系统在内的许多应用中，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，以控制非常大的系统集合，以实现共同目标，而不受网络和物理限制。作为应用，将考虑电力负荷控制问题，其目标是协调数以千计的空调和冰箱等小型电力负荷的电力消耗，以帮助电网在不给电力消费者带来不便的情况下平衡供需，并同时尊重配电网的物理限制。研究成果将支持更多风能和太阳能的整合，改善电网的环境和健康影响。教育和外展活动将涉及K-12、本科生和研究生以及来自当地电力公司的利益相关者。所考虑的问题的主要特征是大量动态的几乎脱钩的系统。每个系统都有自己的本地要求和约束，并通过对其集体行为的要求将它们联系在一起。将开发一种能够处理软性能要求并允许在上层进行适应性的双层控制体系结构，以保证在较低层满足硬安全要求。低层将利用系统的结构属性对称性和要求，特别是排列不变性，以实现高度可扩展的综合方法，以确保安全性。为了安全起见，当控制输入被覆盖时，上层将利用适应/学习来提高系统性能。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势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.