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A System Identification Method to Hammerstein Model Based on Recursive Least Squares Method

Jiangtao Zhai; Chengming Zhu
In this paper, the nonlinear system is taken as the research problem. Hammerstein model as a typical nonlinear model with specific structure, the model is consisting of the static nonlinear module and the linear dynamic module in series form. It can be better reflecting the characteristics of the process, and the Hammerstein model also can be described a large class of nonlinear processes. At present, many scholars have been studied a lot about nonlinear systems and it also proposed some algorithms, thus, a model method based on the recursive least squares algorithm is proposed in this paper, and use the MATLAB simulation software to simulate. Finally, the algorithm was verified by experiments in the accuracy of parameter identification and the advantage of noise resistance.
Select Volume / Issues:
Year:
2016
Type of Publication:
Article
Keywords:
System Identification; Hammerstein Model; Recursive Least Squares; Simulation
Journal:
IJECCE
Volume:
7
Number:
3
Pages:
184-186
Month:
May
ISSN:
2249-071X
Hits: 1017

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