ABSTRACT

The weighting factor adjustment limits the extensive application of conventional model predictive torque control in practice. In this paper, a model predictive torque control strategy with gravitational search algorithm (GSA) is proposed. The detail of an adaptive torque variable is introduced to control the flux linkage of the induction motor, and a modified value function is constructed by using electromagnetic torque and image torque. The proposed model uses two control variables to replace the torque and flux variables in the conventional model predictive torque control and improve the control efficiency. The simulation and experimental results show that the proposed method achieves a fast dynamic performance compared to the conventional model and reduces the average switching frequency. Besides, the system has high response speed, high accuracy, stability, and a certain application value.

摘要

加权因子调整限制了传统模型预测转矩控制在实践中的广泛应用。本文提出了一种基于重力搜索算法（GSA）的模型预测转矩控制策略。引入自适应转矩变量的细节来控制感应电机的磁链，并利用电磁转矩和镜像转矩构造修正值函数。该模型使用两个控制变量来代替传统模型预测转矩控制中的转矩和磁通变量，提高了控制效率。仿真和实验结果表明，与传统模型相比，该方法实现了快速的动态性能，并降低了平均开关频率。此外，系统响应速度快，