Optimal Sliding Mode Control of Modular Multilevel Converters Considering Control Input Constraints

This paper investigates the optimal sliding mode control (SMC) of modular multilevel converters (MMCs) by considering control input constraints. Conventional SMC methods for MMCs typically overlook the system’s constraints. To address this, an optimal SMC approach that incorporates control input constraints through quadratic programming (QP) is proposed. The control design problem is formulated in a constrained optimization framework and solved using the infeasible active-set (IAS) method to efficiently achieve the optimal solution. By applying optimal SMC, this work contributes to the advancement of SMC strategies for MMCs by addressing both constraints and performance optimization in a systematic way. This is particularly relevant for real-world applications, where controllers may temporarily exceed their limits before enforcing constraints. To validate the proposed approach, a comparative analysis with conventional SMC methods is performed, and simulation results confirm that the proposed approach provides improved performance.

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Publication Details

Journal
Energies
Published
2025-05-26
DOI
https://doi.org/10.3390/en18112757
Citations
6
Primary Topic
HVDC Systems and Fault Protection
Type
article
Field-Weighted Citation Impact
4.38

Funders

Controls
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article

Optimal Sliding Mode Control of Modular Multilevel Converters Considering Control Input Constraints

Ahmed El Hajjaji, Homa Sheikhi Jouybary, Davood Arab Khaburi, Augustin Mpanda Mabwe
6 citations
Energies
HVDC Systems and Fault Protection
4.38
article

Optimal Sliding Mode Control of Modular Multilevel Converters Considering Control Input Constraints

Ahmed El Hajjaji, Homa Sheikhi Jouybary, Davood Arab Khaburi, Augustin Mpanda Mabwe
article en
6 citations

Abstract

This paper investigates the optimal sliding mode control (SMC) of modular multilevel converters (MMCs) by considering control input constraints. Conventional SMC methods for MMCs typically overlook the system’s constraints. To address this, an optimal SMC approach that incorporates control input constraints through quadratic programming (QP) is proposed. The control design problem is formulated in a constrained optimization framework and solved using the infeasible active-set (IAS) method to efficiently achieve the optimal solution. By applying optimal SMC, this work contributes to the advancement of SMC strategies for MMCs by addressing both constraints and performance optimization in a systematic way. This is particularly relevant for real-world applications, where controllers may temporarily exceed their limits before enforcing constraints. To validate the proposed approach, a comparative analysis with conventional SMC methods is performed, and simulation results confirm that the proposed approach provides improved performance.

EnergiesVol. 18(11)
Université de Picardie Jules Verne (FR), Iran University of Science and Technology (IR)
Région Hauts-de-France
Openalex Percentile: Top 6%
HVDC Systems and Fault Protection
4.38
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