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神经网络智能控制系统中辨识网络设计方法的探讨
引用本文:陈祥光,黄聪明,薛锦诚,傅若农.神经网络智能控制系统中辨识网络设计方法的探讨[J].计算机仿真,2000,17(4):36-38,51.
作者姓名:陈祥光  黄聪明  薛锦诚  傅若农
作者单位:北京理工大学!100081
摘    要:该文将人工神经网络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。

关 键 词:神经网络  参考模型  系统辨识  智能控制系统

Research on Identifying Networks in Intelligent Control System Based on Neural Networks
Chen Xiangguang,Huang Congming,Xue Jincheng,Fu Ruonong.Research on Identifying Networks in Intelligent Control System Based on Neural Networks[J].Computer Simulation,2000,17(4):36-38,51.
Authors:Chen Xiangguang  Huang Congming  Xue Jincheng  Fu Ruonong
Abstract: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.
Keywords:Neural  networks  BP algorithm Adaptive control Reference model System identification
本文献已被 CNKI 维普 万方数据 等数据库收录!
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