Identification of LPV Models with Non-uniformly Spaced Operating Points by Using Asymmetric Gaussian Weights

Jie You; Qinmin Yang; Jiangang Lu; Youxian Sun

doi:10.1016/j.cjche.2014.05.002

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Identification of LPV Models with Non-uniformly Spaced Operating Points by Using Asymmetric Gaussian Weights

PROCESS MODEL | Updated：2026-01-06

- Identification of LPV Models with Non-uniformly Spaced Operating Points by Using Asymmetric Gaussian Weights
- Identification of LPV Models with Non-uniformly Spaced Operating Points by Using Asymmetric Gaussian Weights
- 中国化学工程学报（英文版） 2014年22卷第7期页码：795-798
- Affiliations：
  
  State Key Laboratory of Industrial Control Technology, Department of Control Science and Engineering, Zhejiang University,Hangzhou,China,310027
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2014.05.002
  中图分类号：
- 纸质出版：2014
- Accepted：
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Jie You, Qinmin Yang, Jiangang Lu, 等. Identification of LPV Models with Non-uniformly Spaced Operating Points by Using Asymmetric Gaussian Weights[J]. 中国化学工程学报（英文版）, 2014,22(7):795-798.

Jie You, Qinmin Yang, Jiangang Lu, Youxian Sun. Identification of LPV Models with Non-uniformly Spaced Operating Points by Using Asymmetric Gaussian Weights[J]. , 2014, 22(7): 795-798.
Jie You, Qinmin Yang, Jiangang Lu, 等. Identification of LPV Models with Non-uniformly Spaced Operating Points by Using Asymmetric Gaussian Weights[J]. 中国化学工程学报（英文版）, 2014,22(7):795-798. DOI： 10.1016/j.cjche.2014.05.002.

Jie You, Qinmin Yang, Jiangang Lu, Youxian Sun. Identification of LPV Models with Non-uniformly Spaced Operating Points by Using Asymmetric Gaussian Weights[J]. , 2014, 22(7): 795-798. DOI： 10.1016/j.cjche.2014.05.002.

摘要

Abstract

In this paper

asymmetric Gaussian weighting functions are introduced for the identification of linear parameter varying systems by utilizing an input-output multi-model structure. It is not required to select operating points with uniform spacing andmore flexibility is achieved. To verify the effectiveness of the proposed approach

severalweighting functions

including linear

Gaussian and asymmetric Gaussianweighting functions

are evaluated and compared. It is demonstrated through simulations with a continuous stirred tank reactor model that the proposed approach provides more satisfactory approximation.

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