Model-free adaptive control of superheated steam temperature based on quantum-behaved particle swarm optimization

YANG Yanxi; XIE Zhouhua; DENG Yi

English

您当前的位置：

首页 >

文章列表页 >

Model-free adaptive control of superheated steam temperature based on quantum-behaved particle swarm optimization

Thermal Power Generation Vol. 45, Issue 4, Pages: 84-88(2016)

更新时间：2025-09-28

- Model-free adaptive control of superheated steam temperature based on quantum-behaved particle swarm optimization
- 作者机构：
  
  西安理工大学自动化与信息工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM621
- Published：2016
- 稿件说明：
移动端阅览
YANG Yanxi, XIE Zhouhua, DENG Yi. Model-free adaptive control of superheated steam temperature based on quantum-behaved particle swarm optimization[J]. Thermal Power Generation, 2016, 45(4): 84-88.
DOI：

YANG Yanxi, XIE Zhouhua, DENG Yi. Model-free adaptive control of superheated steam temperature based on quantum-behaved particle swarm optimization[J]. Thermal Power Generation, 2016, 45(4): 84-88. DOI：

摘要

火力发电厂锅炉过热蒸汽温度不仅具有大滞后特性

且其模型还会随锅炉负荷的变化而变化

故依赖数学模型设计的PID控制一直未取得较好的控制品质。对此

本文提出一种基于量子粒子群的改进无模型自适应控制(QPSO-IMFAC)算法

摆脱了对模型的依赖

利用量子粒子群(QPSO)算法对IMFAC算法控制参数寻优

解决了传统无模型自适应控制(MFAC)算法控制参数难以确定的问题。仿真结果表明:采用QPSO-IMFAC算法控制锅炉过热蒸汽温度时

系统具有强扰动抑制性和高鲁棒性

QPSO-IMFAC算法对锅炉过热蒸汽温度控制是有效的;对阶跃响应和定值扰动的控制效果均优于QPSO-PID算法。因此

可以将IMFAC算法实现于DCS控制中

且使用QPSO-IMFAC算法优化出的控制参数可作为锅炉过热蒸汽温度调节的基准值。

Abstract

The temperature of superheated steam of boiler in thermal power plants has large delay property

and its model changes with the boiler load

which causes the PID controller designed on the basis of mathematical model can not realize good control effects.Against this problem

this paper proposes an improved model free adaptive control algorithm based on quantum-behaved particle swarm optimization(QPSO-IMFAC).This algorithm gets rid of the dependence on the model.Using the quantum-behaved particle swarm optimization(QPSO)algorithm to find the optimal control parameters of the improved model free adaptive control algorithm(IMFAC)can overcomes the shortcomings that the parameters of the conventional MFAC algorithm are difficult to be ascertained.The simulation test result shows that

the boiler system has strong anti-disturbance ability and high robustness when using the QPSO-IMFAC algorithm to control the superheated steam temperature

indicating the QPSO-IMFAC algorithm is superior to the conventional QPSO-PID algorithm in step response and set value disturbance control.

关键词

Keywords

references

Views

186

下载量

CSCD

Alert me when the article has been cited

提交

Publicity Resources

Parameter optimization of active disturbances rejection controller based on seeker optimization algorithm

STUDY ON ESTABLISHING DYNAMIC MODEL OF HEAT RECOVERY BOILER BY USING SEQUENTIAL MODULAR METHOD

A METHOD OF SIGNAL PROCESSING FOR MEASURING PRESSURE IN THE FURNACE

SIMULATION OF UNIT COORDINATED CONTROL SYSTEM(UCCS) BASED ON SOFTWARE BLINK

MATHEMATIC MODEL AND DYNAMIC CHARACTERISTICS OF ONCE-THROUGH BOILER FOR A 300 MW UNIT

Related Author

ZHOU Zhigang

MA Yongguang

DONG Zijian

GAO Zhicun

MAO Xiao-fei

REN Ting-jin

ZHAO Jingfeng

XIN Jianhua

Related Institution

Simulation Control Laboratory of Electric Power Science Research Institute of State Grid Hebei Electric Power Co., Ltd

School of Control and Computer Engineering, North China Electric Power University

Tsinghua University, Tsinghua University Beijing 100084

Hanfeng Power Plant Shanghai

AI问答

⁰