Work

Indirect Model Predictive Control for Capacitor Energy Control in Modular Multilevel Converters

Year: 2025

Type: conference-paper

Abstract: Model predictive control (MPC) has emerged as a promising approach for the control of systems with complex, nonlinear dynamics, such as the control of modular multilevel converters (MMCs). However, despite the intrinsic nonlinear nature of MMCs, linear MPC is predominantly applied, often without a thorough analysis of how the nonlinearities of the MMC affect control performance and constraint compliance. This paper identifies the impacts of the nonlinearities of the MMC on the control performance of linear MPC and proposes a cascaded approach to mitigate these impacts. The proposed approach ensures that the system constraints can still be met when linear MPC is applied to the nonlinear MMC. The performance of the cascaded MPC strategy is validated by highfidelity MATLAB/Simulink simulations and compared to state-of-the-art MPC implementations.

Source: Proceedings of the Annual Conference of the IEEE Industrial Electronics Society

DOI: 10.1109/iecon58223.2025.11220998

Authors: Leonardo Testa, Christoph M. Hackl, Petros Karamanakos

Institutions: Munich University of Applied Sciences, Tampere University

Language: English

Topic: HVDC Systems and Fault Protection

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: gold

Funder: Deutsche Forschungsgemeinschaft