神经网络PID控制器在油田标定间上的应用

Application of neural network PID controller to the calibration shop of oilfield

根据神经网络需要训练学习的特点 ,探索了神经网络PID控制器的实际应用技术 ,在学习阶段采用固定PID参数的控制器 ,在训练结束后实行实时调整PID参数的策略 .将神经网络PID控制器用于油田模拟装置的实际控制 ,结果表明 ,系统的超调量减小 ,准确性提高 ,鲁棒性增强 .

In the paper,the research was made for the real applicable technology of the neural network. Because the neural network need to be trained and learned, thus during learning, fixed parameters were used by controller. After training, the PID parameters were adjusted to real time by the neural network. The above controller was used successfully by the oil field simulating device. The system's overshoot was reduced, accuracy and robustness was improved. The application provides the experience for the neural network on the production processing in industrial applications.