为了便于进行形象化的理解，本章进行了控制结果的可视化编程。利用Matlab与Borland C++ Builder的程序开发接口，通过建立独立的可执行程序，演示了控制过程中对熨平板进行调节的过程。最终认为，PID控制和人工神经网络控制对控制速度和精度都有了很多的改善；对摊铺机自动调平装置而言，其控制器的设计占有重要的地位。 -To facilitate figurative understanding of this chapter for the control of the results

里面有2个模型，一个是用单神经源来实现PID控制，一个是用BP神经网络实现PID控制。都是用S函数实现。-There are two models, one is to realize PID control with single neural source, one is to use the BP neural network to realize PID control. Is using S function implementation.

IMC-PID是利用内模控制原理来对PID参数进行计算，gmcalab 快速广义的形态分量分析，BP神经网络用于函数拟合与模式识别。- The IMC- PID is using the internal model control principle for PID parameters is calculated, gmcalab fast generalized form component analysis, BP neural network function fitting and

是一种双隐层反向传播神经网络，Pisarenko谐波分解算法,IMC-PID是利用内模控制原理来对PID参数进行计算。- Is a two hidden layer back propagation neural network, Pisarenko harmonic decomposition algorithm, The IMC- PID is using the internal model control principle for PID parameters is calculate

使用Matlab实现了基于模糊神经网络的PID控制器，用于模拟斩波电路的PID控制器控制模拟(The PID controller based on fuzzy neural network is realized by using MATLAB, which is used to simulate the control of the PID controller of the analog chopper circuit.)