控制理论(社会学)
模型预测控制
稳健性(进化)
补偿(心理学)
电压
国家观察员
计算机科学
工程类
控制工程
控制(管理)
物理
非线性系统
化学
电气工程
基因
人工智能
量子力学
生物化学
心理学
精神分析
作者
Yang Nan,Shuo Zhang,Xueping Li,Xuerong Li
标识
DOI:10.1109/jestpe.2022.3192883
摘要
Deadbeat predictive current control (DPCC) has been widely used in the field of permanent magnet synchronous motor current control due to its fast dynamic response, good current followability, and a small amount of calculation. However, the accuracy of its predictive model depends heavily on the accuracy of motor parameters. When the motor parameters are mismatched due to temperature changes and magnetic saturation during operation, the robustness of its control is greatly reduced. Based on the above reasons, model-free deadbeat predictive current control with Luenberger disturbance observer (MFDPCC-LDO) method is proposed in this article. This method uses the LDO without motor parameters to estimate the total disturbance of the system, then calculates the predictive control voltage combined with the ultralocal model, and performs delay compensation. It only needs the input and output of the system and the determination of three control parameters, and it is not affected by motor parameter mismatch, and internal and external interference. The simulation and experimental results verify the effectiveness of the improved MFDPCC + LDO method.
科研通智能强力驱动
Strongly Powered by AbleSci AI