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A Control Lyapunov Approach to Finite Control Set Model Predictive Control for Permanent Magnet Synchronous Motors

机译:永磁同步电动机有限控制集模型预测控制的控制Lyapunov方法

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摘要

In this paper, we present a novel model predictive control (MPC) scheme that incorporates stability information derived from a control Lyapunov function (CLF) to dynamically prune suboptimal sequences from the search space and decrease the computational burden placed on the controller. The CLF used for pruning is then incorporated into a cost function that penalizes energy in the error system as well as energy loss due to switching. Despite the very small control periods allowed due dynamic pruning, experimental results are given, showing the resulting controller generates low switching frequencies and low total harmonic distortion.
机译:在本文中,我们提出了一种新颖的模型预测控制(MPC)方案,该方案结合了从控制Lyapunov函数(CLF)导出的稳定性信息,以动态修剪搜索空间中的次优序列,并减少了控制器上的计算负担。然后将用于修剪的CLF合并到成本函数中,该函数会惩罚错误系统中的能量以及由于切换导致的能量损失。尽管由于动态修剪而允许的控制周期非常小,但仍给出了实验结果,结果表明所产生的控制器产生了较低的开关频率和较低的总谐波失真。

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