Recursive Subspace Identification of AUV Dynamic Model under General Noise Assumption | Zendy

Zheping Yan | Zendy; Di Wu | Zendy; Jiajia Zhou | Zendy; Lichao Hao | Zendy

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Recursive Subspace Identification of AUV Dynamic Model under General Noise Assumption

Author(s) -

Zheping Yan,

Di Wu,

Jiajia Zhou,

Lichao Hao

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/547539

Subject(s) - subspace topology , identification (biology) , noise (video) , control theory (sociology) , nonlinear system , system identification , computer science , algorithm , underwater , artificial intelligence , data modeling , physics , control (management) , quantum mechanics , image (mathematics) , biology , geology , database , oceanography , botany

A recursive subspace identification algorithm for autonomous underwater vehicles (AUVs) is proposed in this paper. Due to the advantages at handling nonlinearities and couplings, the AUV model investigated here is for the first time constructed as a Hammerstein model with nonlinear feedback in the linear part. To better take the environment and sensor noises into consideration, the identification problem is concerned as an errors-in-variables (EIV) one which means that the identification procedure is under general noise assumption. In order to make the algorithm recursively, propagator method (PM) based subspace approach is extended into EIV framework to form the recursive identification method called PM-EIV algorithm. With several identification experiments carried out by the AUV simulation platform, the proposed algorithm demonstrates its effectiveness and feasibility

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