Multivariable decoupling control of aeroengine based on QDRNN

LI Hua-cong; RONG Li-ye; ZHU Yu-bin

Chinese

您当前的位置：

首页 >

文章列表页 >

Multivariable decoupling control of aeroengine based on QDRNN

更新时间：2026-07-07

- Multivariable decoupling control of aeroengine based on QDRNN
- Vol. 22, Issue 11, (2007)
- 作者机构：
  
  西北工业大学动力与能源学院,西安,710072
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2007
- 稿件说明：
移动端阅览
LI Hua-cong, RONG Li-ye, ZHU Yu-bin. Multivariable decoupling control of aeroengine based on QDRNN[J]. 2007, 22(11).
DOI：

LI Hua-cong, RONG Li-ye, ZHU Yu-bin. Multivariable decoupling control of aeroengine based on QDRNN[J]. 2007, 22(11). DOI：

摘要

针对航空发动机非线性模型的复杂性

通过对准对角递归神经网络(QDRNN)及梯度下降法(GMD)的分析

研究了基于QDRNN网络的航空发动机多变量解耦PID控制系统.阐明了该算法的结构和原理

通过对设计点及非设计点的仿真.研究表明

QDRNN网络结构相对简单

易于构造训练算法

较好地解决了双变量控制系统中变量之间的耦合作用.

Abstract

Through analysis of QDRNN(quasi-diagonal recurrent neural network) and GMD(gradient decent method)

a multivariable decoupling PID(proportional integral

differential) control system based on QDRNN was presented to resolve the complex nonlinear model of aeroengine.The structure and principle of the algorithm were also illustrated through simulation of design points and non-design points.The research results show that

a multivariable decoupling PIDcontrol system based on QDRNN is well-suited for decoupling of variables in dual-variable control system.

关键词

Keywords

references

Views

390

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Applications of nonlinear backstepping control strategy in multivariable control of aeroengine

Application of Internal Model Control System Based on Neural Network in Aeroengine

Aeroengine Separate Decoupling Control Based on Recursive Neural Networks

Application of adaptive genetic neural network algorithm in design of thrust estimator

Multi-objective optimization of aeroengine PID control based on multi-objective genetic algorithms

Related Author

ZHANG Hai-bo

SUN Jian-guo

SUN Feng-cheng

ZHANG Peng

HUANG Jin-quan

LIU Jian-xun

LI Ying-hong

CHEN Yong-gang

Related Institution

Coollege of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics

College of Energy and power, Nanjing University of Aeronautics and Astronautics

The Engineering Institute, Air Force Engineering University

College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics

School of Power and Energy, Northwestern Polytechnical University, Xi′an

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰