Advances in Optimisation-Based Modulation and Control Techniques for Matrix Converters: A Review

Abstract

Matrix converters have emerged as a promising alternative to traditional power conversion systems, offering advantages such as compact size, high efficiency, and bidirectional power flow. However, their complex topology and stringent operational constraints pose significant challenges for effective modulation and control. This paper provides a comprehensive review of recent advancements in optimization-based modulation and control techniques for matrix converters, highlighting their principles, implementation strategies, and performance impacts. Key methods, including Model Predictive Control (MPC) and Space Vector Modulation (SVM), are discussed, emphasizing their ability to enhance dynamic performance, reduce harmonic distortion, and improve energy efficiency. The paper also explores the integration of advanced optimization algorithms and hybrid control approaches to address system non-linearities and computational constraints. Comparative analyses with traditional techniques underscore the superior efficiency and robustness of optimization-based strategies. The findings suggest that these advancements pave the way for broader adoption of matrix converters in industrial drives, renewable energy systems, and other high-performance applications.