并用这种改进的共轭梯度法对神经网络PID控制器参数实现在线修正。
The parameters of the neural network PID controller are modified on line by the improved conjugate gradient.
本文提出一种由自校正调节器—最小方差控制器（以下简记为STR—MV）的双模控制和在线修正不辨识参数所构成的新的自校正控制方法。
This paper presents a new self-tuning control consisting of a dual mode control by use of STR-MV and the on-line regulation parameter which is unnecessary to be identified.
本文讨论了用焊道表面的温度信息对多个模型参数进行在线修正，提高计算模型的适应性。
The method that on-line identifies parameters of the model through the information of temperature on the welding bead surface and thus increases adaptability of model was discussed in the paper.
应用推荐