FrontSeat Summer School on Embedded Optimal Control

REGISTER HERE

Date: 11-15 September 2023
Location: STU in Bratislava, Slovakia
Contact: juraj.holaza@stuba.sk
Registration deadline: 14^th of July 2023 (no registration fee, limited seats)
Acceptance decision: email was sent to all applicants on 3^rd of August.
(Please contact us if you have not received such email.)
Download: poster
Available Sources: Lectures/Workshops/Photos/Videos

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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.

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