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循环流化床锅炉主汽温的模糊预测函数控制
引用本文:刘吉臻,岳俊红,刘向杰,谭文,房方.循环流化床锅炉主汽温的模糊预测函数控制[J].动力工程,2007,27(4):537-540,644.
作者姓名:刘吉臻  岳俊红  刘向杰  谭文  房方
作者单位:华北电力大学,自动化系,北京,102206
摘    要:循环流化床锅炉主汽温具有大惯性、大滞后和非线性的特性,在特定工况下可以等效为一个具有可测扰动的一阶惯性加纯滞后对象.针对这一典型对象,考虑扰动通道和控制通道纯滞后时间相对大小,基于Smith预估补偿思想,提出了一种可测扰动前馈补偿的预测函数控制算法,结合锅炉负荷调度的T-S模糊模型,设计了循环流化床锅炉主汽温模糊预测函数控制器.仿真结果表明,在不同工况下,模糊预测函数控制器具有良好的设定值跟踪能力和调节性能.该控制方法应用模型简单,计算量小,具有较高的实际应用价值.

关 键 词:自动控制技术  主汽温  预测函数控制  一阶惯性纯滞后  可测扰动  T-S模糊模型
文章编号:1000-6761(2007)04-537-04
修稿时间:2006-07-24

Fuzzy Predictive Functional Control of Fresh Steam Temperature of Circulating Fluidized Bed Boilers
LIU Ji-zhen,YUE Jun-hong,LIU Xiang-jie,TAN Wen,FANG Fang.Fuzzy Predictive Functional Control of Fresh Steam Temperature of Circulating Fluidized Bed Boilers[J].Power Engineering,2007,27(4):537-540,644.
Authors:LIU Ji-zhen  YUE Jun-hong  LIU Xiang-jie  TAN Wen  FANG Fang
Affiliation:Department of Automation, North China University of Electric Power, Beijing 102206, China
Abstract:Fresh steam temperature of circulating fluidized bed boilers are featured by large inertia,long time lag and non-linear behavior;but,under special operating conditions,they can be regarded as equivalent to an object,with first order inertia plus long/delay property,beset with measurable disturbances.According to Smith's ideas of predicted compensation,a predictive functional control(PFC) algorithm with pre-fed compensation,prior to the appearance of measurable disturbances,is proposed,and a fresh steam temperature fuzzy PFC controller for circulating fluidized bed boilers designed,with the help of a load-disposal's T-S fuzzy model.Simulation results indicate that the fuzzy PFC system is featured,by a favorable set-point tractability and a satisfactory governing performance,under various conditions of operation.The algorithm,requiring only a simple model and a small volume of calculation work,has relatively good prospects of practical application.
Keywords:automatic control technique  fresh steam temperature  predictive functional control  first order time lag  measurable disturbance  T-S fuzzy model
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