多步序列模型预测控制的球译码算法
A Sphere Decoding Algorithm for Multistep Sequential Model Predictive Control
摘要：
本文研究了两种模型预测控制概念--顺序模型预测控制和长时间模型预测控制在电力电子系统中的结合。为了实现顺序模型预测控制，优化问题分为两个子问题：第一个总结所有的控制目标，线性依赖于系统的输入。序贯模型预测控制一般要求对第一个子问题获得多个解。由于有限控制集模型预测控制电力电子系统的混合整数性质，本文提出了一种特殊的球形译码器。第二个子问题由所有这些控制目标，非线性依赖于系统的输入，并解决了一个穷举搜索。通过对三电平中点箝位式永磁同步发电机风力发电系统在不同情况下的仿真，并与其他长时域模型预测控制方法进行比较，验证了该方法的有效性
英文摘要：
This paper investigates the combination of two model predictive control concepts, sequential model predictive control and long-horizon model predictive control for power electronics. To achieve sequential model predictive control, the optimization problem is split into two subproblems: The first one summarizes all control goals which linearly depend on the system inputs. Sequential model predictive control generally requires to obtain more than one solution for the first subproblem. Due to the mixed-integer nature of finite control set model predictive control power electronics a special sphere decoder is therefore proposed within the paper. The second subproblem consists of all those control goals which depend nonlinearly on the system inputs and is solved by an exhaustive search. The effectiveness of the proposed method is validated via numerical simulations at different scenarios on a three-level neutral point clamped permanent magnet synchronous generator wind turbine system and compared to otherlong-horizon model predictive control methods
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