4.7 Article

Least squares based iterative identification for a class of multirate systems

期刊

AUTOMATICA
卷 46, 期 3, 页码 549-554

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2010.01.007

关键词

Recursive identification; Parameter estimation; Stochastic gradient; Least squares; Multirate systems

资金

  1. National Natural Science Foundation of China [50876093]
  2. Science and Technology Department of Zhejiang Province, China [2009C34008]
  3. National High-Tech Research & Development Program [2006AA05Z226]

向作者/读者索取更多资源

This paper studies modeling and identification problems for multi-input multirate systems with colored noises. The state-space models are derived for the systems with different input updating periods and furthermore the corresponding transfer functions are obtained. To solve the difficulty of identification models with unmeasurable noises terms, the least squares based iterative algorithm is presented by replacing the unmeasurable variables with their iterative estimates. Finally, the simulation results indicate that the proposed iterative algorithm has advantages over the recursive algorithms. (C) 2010 Elsevier Ltd. All rights reserved.

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