Model-free predictive current control based on improved sliding mode disturbance observer

Qingkun Wei, Cao Tan, Mingji Hao, Xuewei Chen, Yingrui Li, Wenqing Ge
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Abstract

The motor parameters of permanent magnet synchronous motor (PMSM) can be mismatched in operation due to temperature variations and magnetic saturation. The parameter mismatch leads to a significant decrease in the robustness of traditional deadbeat predictive current control (DPCC), which leads to issues such as current static error and motor vibration noise. In this paper, a model-free predictive current control (MFPCC) method based on an improved sliding mode disturbance observer (SMDO) was proposed. The method estimated the total disturbance of the system using the improved SMDO, which could effectively suppress sliding mode chattering and accelerate the convergence speed of current errors. Subsequently, the predicted control voltage was calculated using a hyper-local model and compensated for the time delay. The experimental results demonstrated that the improved MFPCC-SMDO method generated lower motor noise compared to the traditional DPCC method when the controller’s inductance parameters are mismatched.
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基于改进型滑模干扰观测器的无模型预测电流控制
由于温度变化和磁饱和,永磁同步电机(PMSM)的电机参数在运行过程中可能会失配。参数失配导致传统死区预测电流控制(DPCC)的鲁棒性显著下降,从而引发电流静态误差和电机振动噪声等问题。本文提出了一种基于改进的滑模扰动观测器(SMDO)的无模型预测电流控制(MFPCC)方法。该方法利用改进的 SMDO 估算系统的总扰动,可有效抑制滑模颤振,加快电流误差的收敛速度。随后,利用超局部模型计算出预测的控制电压,并对时间延迟进行补偿。实验结果表明,与传统的 DPCC 方法相比,当控制器的电感参数不匹配时,改进的 MFPCC-SMDO 方法产生的电机噪声更低。
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