An Improved Model Predictive Voltage Control for PMSM Drives without Motor Parameters

Xiaoguang Zhang;Ruifang Chen
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Abstract

To address the performance degradation of permanent magnet synchronous motor (PMSM) drives caused by parameter mismatches between actual motor and ideal model in complex industrial environment, an improved model predictive voltage control (I-MPVC) approach without motor parameters is presented in this article. Unlike traditional MPVC where accurate motor parameters are heavily relied on, a motor parameter-independent (MPI) prediction model is constructed to eliminate parameter dependency. Firstly, an incremental voltage prediction model is developed where the influence of resistance and flux linkage mismatches is reduced. Then, an inductance parameter-independent (IPI) factor model, which solely relies on the current and voltage information, is further designed. Besides, the proposed approach takes lower computational complexity, as well as simpler parameter tuning steps, which offers significant benefits for real-time applications in industrial fields. Finally, experiments are conducted to validate the feasibility and superiority of the proposed approach.
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无电机参数永磁同步电机的改进模型预测电压控制
针对复杂工业环境下,由于实际电机参数与理想模型不匹配导致永磁同步电机(PMSM)驱动性能下降的问题,提出了一种改进的无电机参数模型预测电压控制(I-MPVC)方法。与传统MPVC对电机参数的依赖不同,构建了电机参数无关(MPI)预测模型,消除了参数依赖性。首先,建立了一种减少电阻链和磁链不匹配影响的增量电压预测模型;然后,进一步设计了仅依赖电流和电压信息的电感参数无关(IPI)因子模型。此外,该方法具有较低的计算复杂度和较简单的参数调整步骤,为工业领域的实时应用提供了显著的好处。最后,通过实验验证了该方法的可行性和优越性。
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