SCI和EI收录∣中国化工学会会刊

›› 2014, Vol. 22 ›› Issue (7): 795-798.DOI: 10.1016/j.cjche.2014.05.002

• PROCESS MODEL • 上一篇    下一篇

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

Jie You, Qinmin Yang, Jiangang Lu, Youxian Sun   

  1. State Key Laboratory of Industrial Control Technology, Department of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
  • 收稿日期:2013-06-05 修回日期:2013-11-12 出版日期:2014-07-28 发布日期:2014-08-23
  • 通讯作者: Jiangang Lu
  • 基金资助:
    Supported by the National Natural Science Foundation of China (21076179, 61104008), and National Basic Research Program of China (2012CB720500).

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

Jie You, Qinmin Yang, Jiangang Lu, Youxian Sun   

  1. State Key Laboratory of Industrial Control Technology, Department of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
  • Received:2013-06-05 Revised:2013-11-12 Online:2014-07-28 Published:2014-08-23
  • Supported by:
    Supported by the National Natural Science Foundation of China (21076179, 61104008), and National Basic Research Program of China (2012CB720500).

摘要: 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.

关键词: Identification, Multi-model linear parameter varying system, Asymmetric Gaussian weight, Continuous stirred tank reactor

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.

Key words: Identification, Multi-model linear parameter varying system, Asymmetric Gaussian weight, Continuous stirred tank reactor