Model recovery for Hammerstein systems using the hierarchical orthogonal matching pursuit method

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:345

Article

Wang, Dongqing^1,3  Yan, Yaru¹  Liu, Yanjun²  Ding, Junhang^1,3 

[1] Qingdao Univ, Coll Automat & Elect Engn, Qingdao 266071, Peoples R China

[2] Jiangnan Univ, Sch Internet Things Engn, Wuxi 214122, Peoples R China

[3] Collaborat Innovat Ctr Ecotext Shandong Prov, Qingdao 266071, Peoples R China

关键词: Hierarchical identification principle;    Hammerstein system;    Orthogonal matching pursuit (OMP);    Compressed sensing (CS);    Parameter estimation;   

DOI  :  10.1016/j.cam.2018.06.016

来源: Elsevier

【 摘 要 】

Most papers concentrate on the parameter identification of Hammerstein systems with known orders. This paper, motivated by the recent developments in sparse approximations, investigates the combined parameter and order determination of Hammerstein systems. The methodology used relies on greedy schemes-the orthogonal matching pursuit (OMP) algorithm in the compressive sensor (CS) theory. In particular, the first step recasts a bilinear Hammerstein system into two fictitious pseudo-regressive sub-systems which respectively contain the parameters of the nonlinear part or the parameters of the linear part by the hierarchical identification principle. The second step adopts a hierarchical orthogonal matching pursuit (H-OMP) selection procedure to interactively select the parameters and orders of the two sub-systems under the frame of the compressive sensor. Finally, the proposed algorithm is tested on a simulation example. (C) 2018 Elsevier B.V. All rights reserved.

【 授权许可】

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