基于模糊神经网络的高精度电机自抗扰控制

Active Disturbance Rejection Control of High Precision Motor Based on Fuzzy Neural Network

针对太赫兹雷达系统中伺服电机采用PID方法控制精度不高、鲁棒性较弱,及采用自抗扰控制方法参数难以确定等缺点,提出了一种利用模糊神经网络的自适应学习的优点来调节自抗扰控制参数的高精度电机控制方法。首先建立了基于模糊神经网络的自抗扰控制的电机模型,然后分别对该模型和普通PID模型进行了系统仿真和实验测试。结果表明,该方法能显著提高电机的控制精度和鲁棒性。

Aiming at the shortcomings of the PID control of the servo motor in the terahertz radar system,such as low precision and weak robustness,and the trouble in assuring the ADRC control parameters,an automatic anti-interference method based on fuzzy neural network is proposed.Firstly,the motor model of auto disturbance rejection control based on fuzzy neural network is established.Then the system simulation and experimental test are carried out on the model and common PID model.The results demonstrate that the method can significantly improve the control precision and stability of the motor。