神经网络智能控制系统中辨识网络设计方法的探讨

Research on Identifying Networks in Intelligent Control System Based on Neural Networks

该文将人工神经网的基本原理应用于过程控制系统，对辨识网络的基本结构以及网络的训练方法进行了初步探索和总结。在控制系统的辨识网络中应用基本ＢＰ算法与加动量项的ＢＰ算法、随机设置初值与训练设置初值、带参考模型与无参考模型对系统过渡过程特性的影响作了一定的比较与分析。仿真结果表明：所采用的改善网络自适应能力的方法，在不同程度上对系统的调节品质均有相应的改善。

This paper applies the basic principle of neural networks to process control system, and has summarized the basic structures of the networks to be identified and the methods of training networks, basic BP algorithm and improved BP algorithm, setting random initial values and training initial values, having reference model and no reference model are compared and analyzed in the Process control system. The simulation research indicates that above- mentioned methods to improve the performances of control system are effective indeed.