Open AccessAdaptive backstepping complementary sliding mode control with parameter estimation and dead‐zone modification for PMLSM servo system
Author(s) -
Jin Hongyan,
Zhao Ximei,
Wang Tianhe
Publication year - 2021
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/pel2.12063
Subject(s) - control theory (sociology) , backstepping , robustness (evolution) , sliding mode control , lyapunov function , servo , adaptive control , servomotor , robust control , computer science , dead zone , servomechanism , lyapunov stability , control engineering , engineering , control system , nonlinear system , control (management) , physics , artificial intelligence , electrical engineering , biochemistry , chemistry , oceanography , quantum mechanics , geology , gene
An adaptive backstepping complementary sliding mode control (ABCSMC) with dead‐zone parameter modification applicable to the permanent magnet linear synchronous motor is proposed in order to achieve high‐performance servo control fields. On the theoretical foundation of backstepping control and sliding mode control, a strong robust controller, ABCSMC is designed to compensate the uncertainties such as parameter variations and external disturbances occurring in the system. Additionally, an adaptive saturation function is utilized in ABCSMC to avoid the difficulty of parameter selections, so that the optimal parameters can be tuned by the adaptive laws in real time. Moreover, in order to avoid the parameter‐drift phenomenon of the adaptive laws, dead‐zone parameter modification is hereby proposed by setting a performance threshold to solve the overtraining problem. Finally, the stability of the system is proved through Lyapunov theorem and Barbalat's lemma. To investigate the capabilities of the proposed scheme, an experimental platform based on digital signal processor is implemented. The comparison results demonstrate that the proposed controller is capable of achieving higher tracking performance and stronger robustness to uncertainties with respect to parameter variations and external disturbances.