A control strategy for a bearingless induction motor (BL-IM) based on the fuzzy dynamic objective function is proposed in this paper. Firstly, based on the discrete mathematical model of the BL-IM, the stator current and flux linkage are predicted according to the given stator current and flux linkage, the objective function of model predictive current control (MPCC) is designed. Secondly, the fuzzy control algorithm is introduced in the objective function of the MPCC to dynamically assign the weighting factors before the current component on the d-q axis and the influence of the objective function on the performance of the BL-IM is analyzed under different weighting factors. By discretizing the rotational speed deviation Δω and rotational speed deviation rate, fuzzy reasoning is performed to obtain the optimal fuzzy dynamic function. Finally, the optimal fuzzy dynamic function is selected as the objective function of the MPCC to perform the simulations and experiments. The results show that the performance of the BL-IM under the MPCC strategy based on the fuzzy dynamic objective function is improved compared with the traditional MPCC and the vector control based on the fuzzy PID, due to its better dynamic and suspension performance. Meanwhile, the stability of rotor current component is enhanced.

中文翻译：

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基于模糊动态目标函数的无轴承感应电机模型电流预测控制

本文提出了一种基于模糊动态目标函数的无轴承感应电机 (BL-IM) 控制策略。首先，基于BL-IM的离散数学模型，根据给定的定子电流和磁链预测定子电流和磁链，设计模型预测电流控制（MPCC）的目标函数。其次，在MPCC的目标函数中引入模糊控制算法，动态分配dq轴上电流分量前的权重因子，分析不同权重因子下目标函数对BL-IM性能的影响. 通过对转速偏差Δω和转速偏差率进行离散化，进行模糊推理，得到最优的模糊动态函数。最后，选择最优模糊动态函数作为MPCC的目标函数进行仿真和实验。结果表明，基于模糊动态目标函数的MPCC策略下BL-IM的性能比传统的MPCC和基于模糊PID的矢量控制有更好的动态和悬挂性能。同时，增强了转子电流分量的稳定性。