基于BP神经网络的PID控制器

PID Controller Based on BP Neural Networks

利用神经网络和反馈控制理论,提出了一种基于神经网络PID控制器的伺服控制系统结构 在高精度仿真试验转台的应用中证实,该方法避免了PID参数的整定难以匹配的问题,减小了干摩擦对低速运动的影响 实验表明:方法自适应能力强,调节品质好,具有较高的应用价值。

With the advantage of Neural Network and error control, presented the PID servocontroller model basing on BP Neural Network. The principle was applied to turntable for dynamic-simulation-scan-imaging experiment. The technique avoided the question that establishing the PID preference, minished the effect of dry friction at laigh velocity. The simulation results show that the model is satisfied at precision and stable results.