Collaborative Research: Robust-by-Design Networked Dynamical Systems: Bridging the Logic/Analog Divide

未来，高度互联的网络控制系统的脆弱性和弹性是自动驾驶汽车和能源发电/配电网等安全关键应用的主要关注点。必须仔细研究这些关键系统的故障事件，并重新设计系统以避免它们。目前的技术状态涉及耗时且本质上不完整的设计后模拟。该项目的目的是开发理论和计算可扩展的技术，以便这样的系统可以在设计上健壮。我们的方法可以帮助设计具有先验安全保证的更具弹性的组件和系统。我们将开发一个框架，在这个框架中，通过将相互作用建模为事件触发和/或随机耦合来分析网络动态系统。这种动态耦合可以由邻近、遥感或其他成对机制触发，从而导致整个系统的相互作用依赖于状态模式。将给出系统的L2和方差收缩性的稳定性和鲁棒性条件，以及状态相关交互图的代数性质。与基于蒙特卡罗的方法相比，这些条件随系统规模的增加而扩大。在存在外生、对抗和系统不确定性的情况下，控制算法的综合方法将使用该框架进行开发。教育计划包括顶点设计演示和一门新的网络控制系统研究生课程。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。

Fragility and resiliency of future, highly-interconnected networked control system is a major concern for safety-critical applications such as autonomous vehicles and the energy generation/distribution grid. Failure events of such critical systems must be carefully studied, and systems redesigned to avoid them. The current state of the art involves time-consuming and inherently incomplete after-design simulations. The aim of this project is to develop theoretical and computationally scalable techniques so that such systems can be robust-by-design. Our methodology can help design more resilient components and systems with a-priori safety guarantees. We will develop a framework in which networked dynamic systems are analyzed by modeling interactions as event-triggered and/or stochastic couplings. Such dynamical couplings can be triggered by proximity, remote sensing or other pairwise mechanisms resulting in a state-dependent pattern of interactions for the overall system. Stability and robustness conditions will be given in terms of L2 and variance contractivity of systems, and algebraic properties of the state-dependent interaction graph. In contrast to Monte Carlo based methods, such conditions scale well with increasing system size. Synthesis methods for control algorithms with guaranteed performance in the presence of exogenous, adversarial, and system uncertainty will be developed using this framework. The education plan includes capstone design demonstrations and a new graduate level course in networked control systems.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.