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多变量PID型神经元网络控制系统在再热蒸汽温度控制上的仿真
引用本文:程启明,郑勇.多变量PID型神经元网络控制系统在再热蒸汽温度控制上的仿真[J].热力发电,2007,36(9):27-31.
作者姓名:程启明  郑勇
作者单位:1. 上海电力学院,上海,200090
2. 上海大学,上海,200072
基金项目:上海市重点学科建设项目;上海市教委资助项目
摘    要:融合解耦控制理论与神经元网络控制原理,给出了一种多变量的PID型神经网络控制方法。应用所给出的控制算法,对火电厂再热蒸汽温度、低温过热器出口蒸汽温度控制进行了仿真。仿真结果表明,控制算法对再热蒸汽温度控制具有良好的解耦性能和自学习控制特性,当被控对象参数变化时系统具有较强的鲁棒性。

关 键 词:多变量  神经元网络  解耦控制  再热蒸汽温度  PID控制
文章编号:1002-3364(2007)09-0027-05

THE CONTROL SYSTEM OF MULTI-VARIABLE PID NEURON NETWORK AND ITS APPLICATION IN REHEATED STEAM TEMPERATURE CONTROL
CHENG Qi-ming,ZHENG Yong.THE CONTROL SYSTEM OF MULTI-VARIABLE PID NEURON NETWORK AND ITS APPLICATION IN REHEATED STEAM TEMPERATURE CONTROL[J].Thermal Power Generation,2007,36(9):27-31.
Authors:CHENG Qi-ming  ZHENG Yong
Affiliation:1. Shanghai Electric Power College, Shanghai 200090, PRC 2. Shanghai University, Shanghai 200072, PRC
Abstract:A control system of multi-variable PID neuron network has been given by merging the decoupling control theory with the neuron network principle,and the limitations of PID decoupling control in multi-variable control system and the feasibility of intro- ducing the neuron network control system being analysed.A simulation test of temperature control for reheated steam and for outlet steam from the low-temperature superheater has been carried out by using the given control algorithm.Results of simulation show that the said control algorithm has better decoupling performance and self-learning control property for the reheated steam tempera- ture control,and the system has stronger robust in the event of parameters variation concerning the controlled object.
Keywords:multi-variable  neuron network  decoupling control  reheated steam temperature  PID control
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