The PID controller based on BP neural networks is designed to realize control parameter self-learning and self-adjusting.
设计了基于BP神经网络的PID控制器，实现PID控制器参数自学习、自整定。
A parameter self-learning algorithm is presented after defining data structure and variable array to improve the prototype's adaptability to different size of workpieces.
在定义了数据结构和变量数组的基础上，给出了参数自学习过程算法，改善了模型样机对不同规格样本工件的适应性。
The method of establishing on-line temperature prediction model, set point model and parameter tracing self-learning model of computerized heat recovery processing control system is introduced.
介绍了余热处理计算机控制系统的在线温度预报模型、设定模型和参数跟踪自学习模型的建立方法。
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