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

能够适应其环境同时保持安全保证的复杂工程系统在物联网、运输和电力系统等许多应用中至关重要。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，从而在网络和物理限制的情况下实现共同目标。作为一个应用程序，电力负荷控制问题，其中的目标是协调成千上万的小电力负荷，如空调和冰箱的电力消耗，以帮助电网平衡供应和需求，而不影响电力消费者，同时尊重配电网络的物理限制，将被考虑。研究结果将支持更多风能和太阳能的整合，改善电网对环境和健康的影响。教育和推广活动将涉及K-12，本科生和研究生沿着与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本地需求和约束，它们通过关于其集体行为的需求耦合在一起。将开发一种双层控制架构，该架构可以处理软性能要求并允许上层的适应性，并且保证满足下层的硬安全要求。较低级别将利用系统和要求的结构属性对称性，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时，控制输入被覆盖的安全目的。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

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.