Data-driven iterative learning control for continuous-time systems

在这个项目中，我们的目标是开发连续迭代学习控制设计方案，为控制复杂系统提供有效、准确和适用的数据驱动解决方案。该项目建立在两位被提议的主管在迭代学习控制，数据驱动控制和近似理论在数据驱动连续时间控制中的应用方面的广泛研究经验之上。这项研究的主要推动力将是理论，但我们的目标是针对电力电子（并网逆变器）或电机中的具体示范问题。

In this project we aim at developing continuous-time iterative learning control design schemes to provide effective, accurate and applicable data-driven solutions to control complex systems. The project builds on the extensive research experience of the two proposed supervisors in iterative learning control, data-driven control, and applications of approximation theory to data-driven continuous-time control. The main thrust of the research will be theoretical, but we aim to target specific exemplary problems in power electronics (grid-tied inverters) or electrical machines.