Abstract This paper proposes a model predictive torque control scheme for induction machines. The approach utilizes an augmented Lagrangian method in combination with a tailored gradient algorithm to efficiently solve the optimal control problem. The problem formulation accounts for hexagonal voltage constraints as well as constraints on the phase currents and the DC link current. A tailored calculation scheme for energy-efficient current setpoints improves the performance and the stability of the approach. Experimental results with computation times of less than 100 μ s on a d SPACE real-time platform prove the potential of the proposed torque control scheme.

中文翻译：

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用于高性能应用的感应电机的非线性模型预测转矩控制和设定值计算

摘要 本文提出了一种感应电机模型预测转矩控制方案。该方法利用增广拉格朗日方法结合定制的梯度算法来有效地解决最优控制问题。该问题公式考虑了六边形电压约束以及相电流和直流链路电流的约束。针对节能电流设定点的定制计算方案提高了该方法的性能和稳定性。在 ad SPACE 实时平台上计算时间小于 100 μs 的实验结果证明了所提出的扭矩控制方案的潜力。