Finite control set model predictive control (FCS-MPC) is a salient control method for power conversion systems that has recently enjoyed remarkable popularity. Several studies highlight the performance benefits that long prediction horizons achieve in terms of closed-loop stability, harmonic distortions, and switching losses. However, the practical implementation is not straightforward due to its inherently high computational burden. To overcome this obstacle, the control problem can be formulated as an integer least-squares optimization problem, which is equivalent to the closest point search or closest vector problem in lattices. Different techniques have been proposed in the literature to solve it, with the sphere decoding algorithm (SDA) standing out as the most popular choice to address the long prediction horizon FCS-MPC. However, the state of the art in this field offers solutions beyond the conventional SDA that will be described in this article alongside future trends and challenges in the topic.

中文翻译：

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电源转换器和驱动器的长期预测范围 FCS-MPC

有限控制集模型预测控制（FCS-MPC）是一种用于功率转换系统的显着控制方法，最近受到了极大的欢迎。多项研究强调了长预测范围在闭环稳定性、谐波失真和开关损耗方面的性能优势。然而，由于其固有的高计算负担，实际实施并不简单。为了克服这个障碍，控制问题可以表述为整数最小二乘优化问题，相当于格中的最近点搜索或最近向量问题。文献中提出了不同的技术来解决它，其中球形解码算法 (SDA) 脱颖而出，成为解决长预测范围 FCS-MPC 的最流行选择。然而，