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Algorithms 2015, 8(3), 366-379; doi:10.3390/a8030366

Identification of Dual-Rate Sampled Hammerstein Systems with a Piecewise-Linear Nonlinearity Using the Key Variable Separation Technique

1
College of Automation Engineering, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
2
College of Engineering, Ocean University of China, 238 Songling Road, Qingdao 266100, China
*
Author to whom correspondence should be addressed.
Academic Editor: Henning Fernau
Received: 5 May 2015 / Revised: 9 June 2015 / Accepted: 15 June 2015 / Published: 24 June 2015
View Full-Text   |   Download PDF [283 KB, uploaded 24 June 2015]   |  

Abstract

The identification difficulties for a dual-rate Hammerstein system lie in two aspects. First, the identification model of the system contains the products of the parameters of the nonlinear block and the linear block, and a standard least squares method cannot be directly applied to the model; second, the traditional single-rate discrete-time Hammerstein model cannot be used as the identification model for the dual-rate sampled system. In order to solve these problems, by combining the polynomial transformation technique with the key variable separation technique, this paper converts the Hammerstein system into a dual-rate linear regression model about all parameters (linear-in-parameter model) and proposes a recursive least squares algorithm to estimate the parameters of the dual-rate system. The simulation results verify the effectiveness of the proposed algorithm. View Full-Text
Keywords: Hammerstein system; dual-rate; key variable separation technique; polynomial transformation; least squares Hammerstein system; dual-rate; key variable separation technique; polynomial transformation; least squares
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Wang, Y.-Y.; Wang, X.-D.; Wang, D.-Q. Identification of Dual-Rate Sampled Hammerstein Systems with a Piecewise-Linear Nonlinearity Using the Key Variable Separation Technique. Algorithms 2015, 8, 366-379.

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