recursive least-squares estimation for hammerstein nonlinear systems with nonuniform sampling
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2013
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Abstract
This paper focuses on the identification problem of Hammerstein nonlinear systems with nonuniform sampling. Using the key-term separation principle, we present a discrete identification model with nonuniform sampling input and output data based on the frame period. To estimate parameters of the presented model, an auxiliary model-based recursive least-squares algorithm is derived by replacing the unmeasurable variables in the information vector with their corresponding recursive estimates. The simulation results show the effectiveness of the proposed algorithm.
| Reference Key |
li2013mathematicalrecursive
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|---|---|
| Authors | ;Xiangli Li;Lincheng Zhou;Ruifeng Ding;Jie Sheng |
| Journal | journal of power sources |
| Year | 2013 |
| DOI |
10.1155/2013/240929
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