基于改进回声状态网络的游离氧化钙预测控制

李德健; 刘浩然; 刘彬; 刘泽仁; 王卫涛; 闻岩

doi:10.11949/0438-1157.20190716

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基于改进回声状态网络的游离氧化钙预测控制

过程系统工程 | 更新时间：2026-07-24

- 基于改进回声状态网络的游离氧化钙预测控制
- Predictive control of free calcium oxide based on improved echo state network
- 化工学报 2019年70卷第12期页码：4749-4759
- 作者机构：
  
  1.燕山大学电气工程学院，河北秦皇岛 066004
  2.燕山大学信息科学与工程学院，河北秦皇岛 066004
  3.燕山大学机械工程学院，河北秦皇岛 066004
- 作者简介：
  
  李德健（1994—），男，硕士研究生，501807366@qq.com
  刘浩然（1980—），男，硕士，教授，haoranliuysu@163.com
- 基金信息：
  
  河北省自然科学基金项目(F2019203320;E2018203398);国家自然科学基金项目(51641609)
- DOI：10.11949/0438-1157.20190716
  中图分类号： TP 183
- 收稿：2019-06-25，
  
  修回：2019-07-29，
  
  网络首发：2020-06-09，
  
  纸质出版：2019-12-05
- 稿件说明：
移动端阅览
李德健, 刘浩然, 刘彬, 刘泽仁, 王卫涛, 闻岩. 基于改进回声状态网络的游离氧化钙预测控制[J]. 化工学报, 2019, 70(12): 4749-4759

LI Dejian, LIU Haoran, LIU Bin, LIU Zeren, WANG Weitao, WEN Yan. Predictive control of free calcium oxide based on improved echo state network[J]. CIESC Journal, 2019, 70(12): 4749-4759
李德健, 刘浩然, 刘彬, 刘泽仁, 王卫涛, 闻岩. 基于改进回声状态网络的游离氧化钙预测控制[J]. 化工学报, 2019, 70(12): 4749-4759 DOI： 10.11949/0438-1157.20190716.

LI Dejian, LIU Haoran, LIU Bin, LIU Zeren, WANG Weitao, WEN Yan. Predictive control of free calcium oxide based on improved echo state network[J]. CIESC Journal, 2019, 70(12): 4749-4759 DOI： 10.11949/0438-1157.20190716.

摘要

在非线性时延水泥烧成系统中，针对传统预测控制方法调节时间长、控制精度不高的问题，提出一种改进的在线型回声状态网络预测控制模型。首先将带有L1范数约束项的递归最小二乘法与回声状态网络相结合构建在线型预测模型，解决传统预测控制模型辨识精度较低、无法进行实时预测的问题；然后基于改进的回声状态网络预测模型，构建预测控制模型结构，并采用具有全局优化能力的粒子群算法进行滚动优化，保证实际输出量快速、准确、平稳地跟随被控量的设定值；最后利用改进的预测控制模型对水泥烧成系统中的游离氧化钙含量进行预测控制仿真实验，结果表明改进的预测控制模型具有良好的性能和应用前景。

Abstract

In the nonlinear time-delay cement burning system

an improved on-line echo state network predictive control model is proposed for the problem that the traditional predictive control method has long adjustment time and low control precision. Therefore

we firstly combine the L1-norm constrained recursive least squares method with the echo state network to construct an on-line prediction model to address these issues. Then

the structure of predictive control model is constructed based on the improved prediction model of echo state network. And particle swarm optimization (PSO) algorithm with global optimization capability is utilized for rolling to ensure that the actual output follows the setting value of the controlled variable quickly

accurately and smoothly. Finally

the simulation prediction experiments of the free calcium oxide content in the cement burning system are conducted using the improved predictive control model. The results show that the improved predictive control model has good performance and application prospects.

关键词

Keywords

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