Open AccessImproving control effort in output feedback sliding mode control of sampled‐data systems
Author(s) -
Nguyen Thang,
Edwards Christopher,
Azimi Vahid,
Su WuChung
Publication year - 2019
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.2018.5080
Subject(s) - control theory (sociology) , robustness (evolution) , sliding mode control , output feedback , computer science , convergence (economics) , noise (video) , mode (computer interface) , control (management) , sampled data systems , control system , control engineering , engineering , nonlinear system , artificial intelligence , biochemistry , chemistry , physics , quantum mechanics , electrical engineering , economics , image (mathematics) , gene , economic growth , operating system
In this study, the problem of output feedback sliding mode control of linear sampled‐data multi‐input–multi‐output systems is considered. Existing sliding mode control schemes can attenuate the influence of an external disturbance by driving system states onto a sliding surface. However, they can exhibit high gains during transients, which can be O ( 1 / T ) where T is the sampling time period. To address this problem, a new strategy, which employs disturbance approximation, is proposed so that the control effort will be O ( 1 ) . The new method avoids deadbeat phenomena and hence, it will be less sensitive to noise. Theoretical analysis is provided to show the convergence and robustness of the proposed method. Simulations were conducted to show the efficiency of the proposed approach.