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The Auxiliary Model Based Hierarchical Estimation Algorithms for Bilinear Stochastic Systems with Colored Noises

  • Chunqiu Guo
  • Longjin WangEmail author
  • Fang Deng
Article
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Abstract

This paper considers the parameter identification for a class of nonlinear stochastic systems with colored noise. An input-output representation is derived by eliminating the state variables in the bilinear system. Based on the obtained identification model, a recursive generalized extend least squares algorithm is proposed by using the auxiliary model identification idea. Moreover, a two-stage recursive generalized extended least squares algorithm is presented to reduce the computational burden by using the hierarchical identification principle and the auxiliary model identification idea, respectively. A stochastic gradient identification algorithm is proposed for comparison. The simulation results show that the proposed algorithms have a good performance in estimating the parameters of the bilinear systems with colored noises.

Keywords

Auxiliary model bilinear system hierarchical identification least squares recursive identification 

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© ICROS, KIEE and Springer 2019

Authors and Affiliations

  1. 1.School of Electrical and Mechanical EngineeringQingdao University of Science and TechnologyQingdaoP. R. China

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