Open AccessIdentification and control for Hammerstein systems with hysteresis non‐linearity
Author(s) -
Gao Xuehui,
Ren Xuemei,
Zhu Changsheng,
Zhang Chengyuan
Publication year - 2015
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2015.0116
Subject(s) - control theory (sociology) , robustness (evolution) , hysteresis , linearity , servomechanism , controller (irrigation) , system identification , robust control , computer science , mathematics , control system , control engineering , engineering , control (management) , physics , measure (data warehouse) , artificial intelligence , quantum mechanics , biology , agronomy , biochemistry , chemistry , database , electrical engineering , gene
Identification and composite control of Hammerstein system with unknown order linear dynamics and a static hysteresis non‐linearity modelled by Preisach operator is investigated. The order of linear dynamics is firstly determined by Hankel matrix approach and then a blind identification is implemented to identify the linear dynamics based on the over‐sampling output measurements only. Then a novel deterministic approach is proposed to identify the Preisach model for hysteresis non‐linearity, which is devoted to identify a triangle matrix. This novel approach needs less dimensions to obtain Preisach density function than other existing methods. Finally, a composite control consisting of discrete inverse model‐based controller (DIMBC) and discrete adaptive sliding mode controller (DASMC) is developed to achieve tracking control. The composite control can reduce the reaching time of DASMC and improve the robustness of DIMBC. Experiments based on a turntable servo system demonstrate the effectiveness of the proposed identification and control methods.