Date: 11-15 September 2023
Location: STU in Bratislava, Slovakia
Contact: juraj.holaza@stuba.skRegistration deadline: 14th of July 2023 (no registration fee, limited seats)
Acceptance decision: email was sent to all applicants on 3rd of August.
(Please contact us if you have not received such email.)
Download: poster
Key Speakers:
- Michal Kvasnica
- Profesor at STU in Bratislava.
- Recognized expert in the field of predictive control.
- Gergely Takács
- Senior research engineer at Garret Motion.
- Recognized expert in the field of real-time embedded control.
- Martin Klaučo
- Deputy of Institute of Information Engineering, Automation, and Mathematics (UIAM) for research at STU in Bratislava.
- Recognized expert in the field of AI.
- Marco Vaccari
- Assistant Professor at University of Pisa (Pisa, Toscana, Italia).
- Recognized expert in the field of process modeling/simulation/optimization.
- Martin Ždímal
- Lecturer of English/Slovak languages with 18-year experience.
- Trainer of soft/hard skills.
Scope: The aim of this 5-day course is to give both theoretical background and hands-on knowledge with advanced methods and tools for embedded optimal control. The course will cover selected state-of-the-art approaches to the formulation and practical solution of optimal control problems, including real-time model predictive control design as well as its data-driven near-optimal alternative using machine learning, with a focus on their implementability on embedded computing hardware. All lecture topics will be accompanied by intensive computer exercises. The second part of the course will introduce the participants to a family of microcontroller-based pocket laboratories integrating various control experiments. Participants will then start to work on a self-chosen application problem by selecting a particular hardware platform and one of the control algorithms presented earlier. Towards the end of the course, they will present the obtained results. Needless to say, a lecture focused on presentation skills will also be part of the course.
Tentative schedule of the summer school
| Mo | Tu | We | Th | Fr | |
| 9:00 – 10:00 |
Registration | Introduction to MPC Code | Introduction to Embedded Control Hardware / Introduction to AutomationShield |
Soft Skills Presentation | Project Presentation |
| 10:00 – 11:00 |
Introduction to Optimal Control / Introduction to MPT3 |
AutomationShield Workshop | |||
| 11:15 – 12:00 |
MPC Code Workshop | ||||
| 12:00 – 13:00 |
Lunch | Lunch | Lunch | Lunch | Lunch |
| 13:00 – 14:00 |
MPT3 Workshop | Introduction to Machine Learning | Project Assignment | Project Work | |
| 14:15 – 17:00 |
Machine Learning Workshop |
Social Program |
Recommended Hotels:
We would like to note that we do not have any special agreements with hoteliers. We encourage students to find their accommodation on their own. We can recommend some hotels that are close and for a reasonable price: Hotel Saffron, Hotel Tatra, Loft Hotel.
