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

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  • Control Theory
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Abstract

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.

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Authors and Affiliations

  1. College of Information Science & Engineering, Northeastern University, Shenyang, 110819, P. R. China

    Bi Zhang & Zhi-Zhong Mao

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  1. Bi Zhang
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  2. Zhi-Zhong Mao
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Correspondence to Zhi-Zhong Mao.

Additional information

Bi Zhang was born in Shenyang, Liaoning Province, China. He is currently studying for a Ph.D. degree at the Northeastern University, Shenyang, China. His main research interests are nonlinear system modeling and control.

Zhi-Zhong Mao received his B.S. degree from Harbin Electrician College, Harbin, China, and his M.S. and Ph.D. degrees from Northeastern University, Shenyang, China, in 1982, 1984, and 1991, respecttively. He is a Professor and a Ph.D. Supervisor at Northeastern University, China. His main research interests are modeling, control and optimization in complex industrial systems.

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Zhang, B., Mao, ZZ. Consistent parameter estimation and convergence properties analysis of hammerstein output-error models. Int. J. Control Autom. Syst. 13, 302–310 (2015). https://doi.org/10.1007/s12555-013-0336-x

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  • DOI: https://doi.org/10.1007/s12555-013-0336-x

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