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Two-Stage Generalized Projection Identification Algorithms for Stochastic Systems

  • Yuanbiao Hu
  • Qin Zhou
  • Hao Yu
  • Zheng Zhou
  • Feng Ding
Short Paper
  • 37 Downloads

Abstract

This paper considers the parameter estimation problem of stochastic systems (i.e., controlled autoregressive systems) by adopting the projection method and the hierarchical identification principle. To improve the performance of the projection identification algorithm, a generalized projection algorithm is proposed by introducing a data window length. By means of the hierarchical identification principle, we divide the system into two fictitious subsystems and derive a two-stage generalized projection identification algorithm. The simulation example tests the effectiveness of the proposed identification algorithms.

Keywords

Parameter estimation Recursive identification Hierarchical identification Gradient search Projection method 

Notes

Acknowledgements

This work was supported by the National Key R&D Program of China (No. 2016YFE0202200) and the Research Foundation of China University of Petroleum-Beijing At Karamay (No. CYJ2017B-01-001).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Key Laboratory of Deep GeoDrilling Technology of Ministry of Natural Resources, School of Engineering and TechnologyChina University of GeosciencesBeijingPeople’s Republic of China
  2. 2.Internet of Things EngineeringJiangnan UniversityWuxiPeople’s Republic of China

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