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时间迭代学习控制设计方案，以提供有效，准确和适用的数据驱动的解决方案来控制复杂的系统。该项目建立在两个建议的主管在迭代学习控制，数据驱动控制，近似理论的应用程序，数据驱动的连续时间控制的广泛研究经验。研究的主要方向是理论，但我们的目标是针对电力电子（并网逆变器）或电机中的特定示例性问题。

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.