人工神经网络(Artificial Neural Network)是从生理角度对智能的模拟，具有极

高的学习能力和自适应能力，能够以任意精度逼近任意函数，完成对系统的仿真；

而遗传算法是对自然界生物进化过程的模拟，具有极强的全局寻优能力，这两种

算法都是当下研究较多的智能方法。将这两种方法与常规的 PID 控制相结合，

构成智能 PID 控制器，使其具有参数自整定、自适应的能力，以适应复杂环境

下的控制要求，这一思路对提高控制效果具有很好的现实意义。

-Artificial Neural Network (ANN) is an imitation of the intelligence by the point of physiological. It has a high capacity of learning and adaptive, can approximate any function to arbitrary accuracy, and complete the simulation of the system. The Genetic

algorithm is a simulation of natural biological evolution, which has a strong ability of

global optimization. These two algorithms are more intelligent method of current

research. The idea of combining these two methods with the conventional PID

controller to be a intelligent controller with the abilities of parameter auto-tuning and

adaptive for the requirements of the complex environment, has a high practical

significance of improving the control effect.