Least-squares based iterative parameter estimation for two-input multirate sampled-data systems

  • Authors:
  • Jing Lu;Xinggao Liu;Feng Ding

  • Affiliations:
  • Control Science and Engineering Research Center, Jiangnan University, Wuxi, P. R. China;College of Information Science and Engineering, Zhejiang University, Hangzhou, P.R. China;Control Science and Engineering Research Center, Jiangnan University, Wuxi, P. R. China

  • Venue:
  • ACC'09 Proceedings of the 2009 conference on American Control Conference
  • Year:
  • 2009

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Abstract

This paper studies identification problems for two-input multirate systems with colored noises (The method in the paper can be easily extended to multi-input multirate systems). The state-space models are derived for the multirate systems with two different input sampling 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 algorithm has good performances.