Zagreb Control Seminar

Šandor Ileš PhD, Associate Professor, University of Zagreb, Faculty of Electrical Engineering and Computing

This talk provides an overview of three distinct applications of Model Predictive Control (MPC) implemented in the Laboratory for Mechatronic Systems, all focused on ensuring system stability inspired by a flexible control Lyapunov function framework. The first case study explores an MPC approach designed to minimize switching losses in a two-level synchronous generator side converter (SGSC). The second application presents an MPC solution for stabilizing a tower crane system with variable cable lengths. The final case discusses MPC-based Direct Yaw Moment Control (DYC) of an electric vehicle. Across all three applications, the talk emphasizes the stability methodologies that optimize performance, supported by both simulation and experimental results.

Marko Švec PhD Student, University of Zagreb, Faculty of Electrical Engineering and Computing

Get ready to discover a groundbreaking approach to (vehicle dynamics) control! This talk will focus on the use of the Koopman operator in model predictive control (MPC) to accelerate vehicle dynamics control algorithms. By using the Koopman operator to create a linear representation of complex nonlinear systems, a new level of control efficiency and simplicity is unlocked. This so-called Koopman-MPC framework transforms challenging nonlinear optimization problems into much simpler quadratic problems, providing a perfect blend of high performance and computational speed.

We will cover the basics of vehicle dynamics and MPC, introduce the exciting theory behind the Koopman operator, and explore state-of-the-art techniques for identifying Koopman models, including extended dynamic mode decomposition (EDMD), deep dynamic mode decomposition (Deep-DMD), and a new method called enhanced extended dynamic mode decomposition (E²DMD). The presentation will show the real-world application of this technology in vehicle control, with demonstrations including a torque vectoring algorithm powered by KMPC and validated by multiple experiments.

Ivan Cvok PhD, Powertrain Controls Lead Engineer, Rimac Technology d.o.o.

This presentation outlines the structured development of automotive control systems following the V-model, from concept to vehicle testing, with a focus on real-world industrial applications. By comparing the development process in an industrial environment to that in research, it will highlight practical challenges and discuss solutions following the V-model. Starting from high-level vehicle requirements, we will delve into the decomposition of system and software architectures, addressing key challenges and interactions during controller design. Special attention will be given to real-time implementation, operational domain considerations, active system interactions, calibration flexibility, and the use of automated code generation alongside CI/CD practices. The presentation will conclude with a comprehensive discussion of testing strategies, from unit testing and model-in-the-loop (MIL) validation to hardware-in-the-loop (HIL) and in-vehicle testing, ensuring robust system validation and performance in real-world scenarios.