Top­ics in Auto­mat­ic Con­trol

This course covers a selection of current topics in automatic control. The initial part of this course will follow a
regular lecture format, while the major part of this course will require active student participation and independent
studies of current research topics in advanced control. The course first briefly summarizes some main concepts
in advanced control and discusses the spectrum between model-free and model-based control approaches. Next,
specific topics will be presented, based on which students select a research article for their major study during the
course. Furthermore, this subject will provide an introduction to academic reading, writing and presentation as
the semester progresses. From the methodological point of view, we will discuss advanced data- and model-based
control methods, and in particular their application to real-world autonomous systems, robotics and multi-agent
systems. The selection of topics may change from year to year.

Example topics are:
1. Data-driven and learning-based control.
2. (Non-linear) model predictive control and its extensions.
3. Advanced trajectory optimization.
4. Robust control.
5. Rollout and Monte-Carlo based control.