Open AccessSliding mode control for non‐linear systems by Takagi–Sugeno fuzzy model and delta operator approaches
Author(s) -
Wang Jiahui,
Gao Yabin,
Qiu Jianbin,
Ki Ahn Choon
Publication year - 2017
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.2016.0231
Subject(s) - control theory (sociology) , delta operator , controller (irrigation) , actuator , fuzzy logic , sliding mode control , linear matrix inequality , fault (geology) , fuzzy control system , operator (biology) , computer science , mode (computer interface) , mathematics , nonlinear system , mathematical optimization , shift operator , control (management) , artificial intelligence , physics , repressor , compact operator , chemistry , operating system , biochemistry , quantum mechanics , transcription factor , programming language , extension (predicate logic) , gene , biology , agronomy , seismology , geology
This study considers the problem of adaptive sliding mode control for discrete‐time Takagi–Sugeno (T–S) fuzzy systems with actuator faults and external disturbances via the delta operator method. The delta operator approach is used to represent the discrete‐time non‐linear systems described by T–S fuzzy models. The actuator fault considered in this study is unknown and its fault‐deviation is also unknown. A reduced‐order system is utilised to design the sliding mode surface subject to linear matrix inequality constraint. By constructing the sliding mode surface, a novel adaptive sliding mode controller is designed to guarantee that the closed‐loop system is uniformly ultimately bounded. Finally, two practical examples are presented to show the effectiveness and applicability of the developed fault‐tolerant control scheme.