Consistent parameter estimation and convergence properties analysis of hammerstein output-error models

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• 作者：Bi Zhang (1)
  Zhi-Zhong Mao (1)
  
  1. College of Information Science & Engineering ; Northeastern University ; Shenyang ; 110819 ; P. R. China
  
• 关键词：Convergence properties ; Hammerstein models ; non ; martingale difference sequence noise ; non ; strictly positive real condition ; on ; line recursive identification ; ordinary differential equation (ODE) method
• 刊名：International Journal of Control, Automation and Systems
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：13
• 期：2
• 页码：302-310
• 全文大小：1,335 KB
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• 刊物类别：Engineering
• 刊物主题：Control Engineering
  
• 出版者：The Institute of Control, Robotics and Systems Engineers and The Korean Institute of Electrical Engi
• ISSN：2005-4092

文摘

This paper presents an on-line bias-compensating recursive least squares (BCRLS) identification algorithm for Hammerstein output-error models disturbed by non-martingale difference sequence noise. By introducing an auxiliary vector uncorrelated with the noise, the consistent parameter estimation is obtained without the strictly positive real (SPR) condition. Convergence analysis of the recursive algorithm is performed using the ordinary differential equation (ODE) method. The simulation results validate the algorithm proposed.