Thrust estimator design based on K-means clustering and reduced least squares support vector regression

ZHAO Yong-ping; SUN Jian-guo; WANG Qian-yu; CHEN Ting-hao

Chinese

您当前的位置：

首页 >

文章列表页 >

Thrust estimator design based on K-means clustering and reduced least squares support vector regression

更新时间：2026-07-07

- Thrust estimator design based on K-means clustering and reduced least squares support vector regression
- Vol. 25, Issue 5, (2010)
- 作者机构：
  
  1. 南京理工大学机械工程院智能弹药技术国家重点实验室,南京,210094
  2. 南京航空航天大学能源与动力学院,南京,210016
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2010
- 稿件说明：
移动端阅览
ZHAO Yong-ping, SUN Jian-guo, WANG Qian-yu, et al. Thrust estimator design based on K-means clustering and reduced least squares support vector regression[J]. 2010, 25(5).
DOI：

ZHAO Yong-ping, SUN Jian-guo, WANG Qian-yu, et al. Thrust estimator design based on K-means clustering and reduced least squares support vector regression[J]. 2010, 25(5). DOI：

摘要

提出了一种基K-均值聚类和约简最小二乘支持向量回归机的推力估计器设计方法.首先用K-均值聚类法将全包线范围内的数据进行聚类

然后在每一个类当中

用迭代约简最小二乘支持向量回归机设计一个子推力估计器.在用迭代约简最小二乘支持向量回归机设计子推力估计器的过程中

为了使计算数值更稳定

用Cholesky分解代替原来的迭代方法.最后仿真实验表明

此推力估计器能满足直接推力控制的需要

并和其它的方案比较起来

该方案存在一定的优势.

Abstract

In this paper

a design scheme for thrust estimator was proposed based on K-means clustering and reduced least squares support vector regression. Firstly

the K-means clustering algorithm was utilized to cluster the data in the full flight envelope

and the

a sub-estimator was designed in each cluster using the recursive reduced least squares support vector regression (RRLSSVR). In the process of designing the sub-estimator with RRLSSVR

the Cholesky factorization was utilized to replace the original iteration method for achieving higher numerical stability. Finally

the simulation experiments show that the thrust estimator can satisfy the requirement of direct thrust control for aeroengines

and as compared with other scheme for thrust estimator

the proposed scheme in this paper is also superior.

关键词

Keywords

references

Views

407

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Fault diagnosis of abnormal fuel injection of small aviation piston engine

Method of compressor characteristic extension combining exponent extrapolation method with support vector machine

Direct thrust control of turbofan engines based on unknown input observer

Method of roller bearing fault diagnosis based on feature fusion of EMD entropy

Fault diagnosis of aero-engine gas path based on SVM and SNN

Related Author

HU Wei

ZHANG Chen

MAO Jianguo

ZHAO Fei

SHEN Huan

翟向博

苏三买

饶高

Related Institution

Command and Control Communication Center,Shanghai Aerospace Electronic Technology Institute

西北工业大学动力与能源学院

Academy of Aeronautic Propulsion Technology, Aviation Industry Corporation of China

School of Energy and Power Engineering,Beijing University of Aeronautics and Astronautics

School of Automatization, Guangdong Polytechnic Normal University

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