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Low-computational-complexity algorithm for current predictive control of an externally excited synchronous machine

机译:用于电流预测控制的低计算 - 复杂算法外部激发同步机的预测控制

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The current control in externally excited synchronous machines employed in applications such as automotive electrical traction drives is a challenging problem. These applications are characterized by fast dynamics that are subject to hard physical constraints including quadratic constraints related to the state and control input. The goal of this paper is to develop a controller synthesis method which can deal with these challenges. To this end, firstly, a polytopic approximation of quadratic constraints is performed. Then, a low-computational-complexity algorithm for current predictive control based on the flexible Lyapunov functions concept is employed by using a one-step-ahead prediction horizon. It is then shown that the resulting current control problem can be transformed into a linear program, which is suitable for an on-line implementation. A realistic simulation scenario is then used to illustrate the effectiveness of the proposed method. The obtained results show significant improvement compared with the existing PI approaches. Moreover, the computational complexity of the algorithm is compatible with hardware requirements of existing electronic control units.
机译:在汽车电气牵引驱动器等应用中使用的外部激发同步机中的电流控制是一个具有挑战性的问题。这些应用程序的特征在于快速动态,该动态受到硬物理约束的,包括与状态和控制输入相关的二次约束。本文的目标是开发一个控制器合成方法,可以处理这些挑战。为此,首先,执行二次约束的多粒逼近。然后,采用基于灵活Lyapunov功能概念的基于灵活的Lyapunov功能概念的低计算 - 复杂性算法,使用一步预测地平线采用。然后示出了所得到的电流控制问题可以转换成线性程序,其适用于在线实现。然后使用现实的模拟场景来说明所提出的方法的有效性。与现有的PI方法相比,所获得的结果表现出显着的改善。此外,算法的计算复杂性与现有电子控制单元的硬件要求兼容。

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