CONTROL OF SUPERHEATED STEAM TEMPERATURE BASED ON RBF NEURAL NETWORK IDENTIFICATION

WANG Tian; XUE Jian-zhong; XI Zhi-yong; ZHAO Kun-jiao; HAO De-feng Xi'an Thermal Power Research Institute Co Ltd

doi:10.19666/j.rlfd.2008.10.025

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CONTROL OF SUPERHEATED STEAM TEMPERATURE BASED ON RBF NEURAL NETWORK IDENTIFICATION

更新时间：2025-09-28

- CONTROL OF SUPERHEATED STEAM TEMPERATURE BASED ON RBF NEURAL NETWORK IDENTIFICATION
- Thermal Power Generation Issue 10, Pages: 87-91(2008)
- 作者机构：
  
  西安热工研究院有限公司
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.2008.10.025
  CLC： TP183;TP273
- Published：2008
- 稿件说明：
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WANG Tian, XUE Jian-zhong, XI Zhi-yong, et al. CONTROL OF SUPERHEATED STEAM TEMPERATURE BASED ON RBF NEURAL NETWORK IDENTIFICATION[J]. Thermal power generation, 2008, (10): 87-91.
DOI：

WANG Tian, XUE Jian-zhong, XI Zhi-yong, et al. CONTROL OF SUPERHEATED STEAM TEMPERATURE BASED ON RBF NEURAL NETWORK IDENTIFICATION[J]. Thermal power generation, 2008, (10): 87-91. DOI： 10.19666/j.rlfd.2008.10.025.

摘要

提出一种基于RBF神经网络辨识的PID串级主蒸汽温度控制策略

即将RBF神经网络与常规PID串级控制相结合构成RBF-PID控制器。该控制器不仅具有常规PID控制器的特性

而且还具有智能控制器的自学习能力

增强了系统对不确定因素的适应性。仿真研究结果表明

RBF-PID控制系统动态调节品质显著优于常规PID串级控制

能适应对象参数的变化

具有较强的鲁棒性和自适应能力。

Abstract

A PID cascade main steam temperature control strategy based on radial basis function (RBF)neural network identification has been put forward

and a RBF-PID controller being constructed by combining RBF neural network with conventional PID cascade control.The said controller not only has the behavior of conventional PID cascade control

but also boasts the self-study ability of an intellegent controller

strengthening the system's adaptability to some uncertain factors.Results of simulation study show that the dynamic performance of RBF-PID control system is substantially superior to that of the convintional PID cascade control

can readily accommodate itself to the variation of object's parameters

having stronger robustness and self-adaptability.

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