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一种改进RBF网络与PID相协调的自适应控制
引用本文:许昌,吕剑虹,程明,郑源.一种改进RBF网络与PID相协调的自适应控制[J].哈尔滨工程大学学报,2007,28(6):660-664.
作者姓名:许昌  吕剑虹  程明  郑源
作者单位:1. 东南大学,电气学院,江苏,南京,210096;河海大学,水电学院,江苏,南京,210098
2. 东南大学,电气学院,江苏,南京,210096
3. 河海大学,水电学院,江苏,南京,210098
基金项目:高等学校博士学科点专项科研项目 , 河海大学校科研和教改项目
摘    要:为充分利用人工神经网络处理非线性问题能力和PID控制器设计简单以及鲁棒性强的优点,设计了高性能控制器.通过对最小资源分配网络的裁剪策略进行改进,使改进的网络具有更加紧凑的结构;把改进的最小资源分配网络应用到神经网络自适应控制器中,同时结合神经网络自适应控制和PID控制,提出一种神经网络与PID相协调的自适应控制策略,并应用到对电站锅炉过热汽温的控制上.仿真结果表明,提出的控制算法与常规的控制算法相比具有更好的控制品质.

关 键 词:最小资源分配网络  神经自适应控制  过热汽温
文章编号:1006-7043(2007)06-0660-05
修稿时间:2006-03-17

Self-adaptive control with coordinated PID and improved RBF network
XU Chang,LU Jian-hong,CHEN Ming,ZHEN Yuan.Self-adaptive control with coordinated PID and improved RBF network[J].Journal of Harbin Engineering University,2007,28(6):660-664.
Authors:XU Chang  LU Jian-hong  CHEN Ming  ZHEN Yuan
Affiliation:1. College of Electrical Engineering, Southeast University, Nanjing 210096, China ; 2. College of Water and Hydropower, Hohai University, Nanjing 210098,China
Abstract:A high performance controller is devised to make full use of neural network capacity in dealing with nonlinear problems by applying a PID controller's advantages of simple design and strong robustness.A PID neural network(PIDNN) control system consists of three hidden layers of proportional(P),integral(I),and derivative(D) neurons.A PIDNN's weights are adjusted by back-propagation algorithms.Through an improved pruning strategy for a minimal resource allocating network(MRAN),the resulting network is made more compact.The improved MRAN is applied to the neural adaptive control(NAC) strategy.Combining NAC with PID control,a self-adaptive control strategy is presented which coordinates the neural network and PID.This strategy was used to simulate control of the superheated steam temperature of a power station boiler.Results show the algorithm performs better than conventional control algorithms.
Keywords:minimal resource allocating network(MRAN)  neural adaptive control(NAC)  superheated steam temperature
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