Identification and control for Hammerstein systems with hysteresis non‐linearity. Issue 13 (1st August 2015)

• Record Type: Journal Article
• Authors: Gao, Xuehui; Ren, Xuemei; Zhu, Changsheng; Zhang, Chengyuan
• Is Part Of: IET control theory & applications. Volume 9:Issue 13(2015)
• Page Start: 1935
• Page End: 1947
• Publication Date: 2015-08-01
• Subjects: identification -- control nonlinearities -- hysteresis -- linear systems -- Hankel matrices -- sampling methods -- discrete time systems -- adaptive control -- variable structure systems; Hammerstein system composite control -- Hammerstein system identification -- hysteresis nonlinearity -- unknown order linear dynamics -- static hysteresis nonlinearity -- Preisach operator -- linear dynamics order -- Hankel matrix approach -- blind identification -- linear dynamics identification -- over‐sampling output measurements -- deterministic approach -- triangle matrix identification -- Preisach density function -- composite control -- discrete inverse model‐based controller -- discrete adaptive sliding mode controller -- DASMC -- tracking control -- reaching time reduction -- DIMBC robustness improvement -- turntable servo system; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2015.0116
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : 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.