SCI和EI收录∣中国化工学会会刊

›› 2014, Vol. 22 ›› Issue (11/12): 1268-1273.DOI: 10.1016/j.cjche.2014.09.028

• 过程系统工程与过程安全 • 上一篇    下一篇

Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition

Hongwei Wang, Tao Liu   

  1. School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China
  • 收稿日期:2014-01-08 修回日期:2014-03-14 出版日期:2014-12-28 发布日期:2014-12-24
  • 通讯作者: Tao Liu
  • 基金资助:
    Supported in part by the National Thousand Talents Program of China, the National Natural Science Foundation of China (61473054), and the Fundamental Research Funds for the Central Universities of China.

Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition

Hongwei Wang, Tao Liu   

  1. School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China
  • Received:2014-01-08 Revised:2014-03-14 Online:2014-12-28 Published:2014-12-24
  • Supported by:
    Supported in part by the National Thousand Talents Program of China, the National Natural Science Foundation of China (61473054), and the Fundamental Research Funds for the Central Universities of China.

摘要: In this paper a recursive state-space model identification method is proposed for non-uniformly sampled systems in industrial applications. Two cases for measuring all states and only output(s) of such a system are considered for identification. In the case of statemeasurement, an identification algorithm based on the singular value decomposition (SVD) is developed to estimate the model parameter matrices by using the least-squares fitting. In the case of output measurement only, another identification algorithm is given by combining the SVD approach with a hierarchical identification strategy. An example is used to demonstrate the effectiveness of the proposed identification method.

关键词: Non-uniformly sampling system, State-space model identification, Singular value decomposition, Recursive algorithm

Abstract: In this paper a recursive state-space model identification method is proposed for non-uniformly sampled systems in industrial applications. Two cases for measuring all states and only output(s) of such a system are considered for identification. In the case of statemeasurement, an identification algorithm based on the singular value decomposition (SVD) is developed to estimate the model parameter matrices by using the least-squares fitting. In the case of output measurement only, another identification algorithm is given by combining the SVD approach with a hierarchical identification strategy. An example is used to demonstrate the effectiveness of the proposed identification method.

Key words: Non-uniformly sampling system, State-space model identification, Singular value decomposition, Recursive algorithm