Research of Dynamic Parameter Identification of LuGre Model Based on Weights Boundary Neural Network | Zendy

Aiqing Huo | Zendy; HE Yu-yao | Zendy; Yan Ruan | Zendy; Nan Tang | Zendy

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Research of Dynamic Parameter Identification of LuGre Model Based on Weights Boundary Neural Network

Author(s) -

Aiqing Huo,

HE Yu-yao,

Yan Ruan,

Nan Tang

Publication year - 2011

Publication title -

energy procedia

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.474

H-Index - 81

ISSN - 1876-6102

DOI - 10.1016/j.egypro.2011.10.317

Subject(s) - identification (biology) , artificial neural network , boundary (topology) , computer science , control theory (sociology) , control engineering , engineering , mathematics , artificial intelligence , mathematical analysis , biology , botany , control (management)

The identification problem on the dynamic parameters in LuGre model is studied. The identification method proposed uses a neural network which considers weights boundary. The network structures and weight adjustment algorithm are given out. In order to find a set of parameters to make it approach the actual one, this algorithm uses neural network identification within the bounds of the identified parameters. Compared with the non-linear least squares (NLS) parameter identification, the relative errors of parameters which are identified by neural network based on weights boundary (WBNN) are smaller, and the precision is higher. Numerical simulation is provided to show the efficiency of the proposed method

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