Open AccessH ∞ fuzzy filter for non‐linear sampled‐data systems under imperfect premise matching
Author(s) -
Kim Ho Jun,
Park Jin Bae,
Joo Young Hoon
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.2016.0240
Subject(s) - control theory (sociology) , fuzzy logic , filter (signal processing) , fuzzy control system , mathematics , imperfect , linear system , filter design , stability (learning theory) , matching (statistics) , computer science , artificial intelligence , control (management) , machine learning , statistics , linguistics , philosophy , computer vision , mathematical analysis
This study proposes an H ∞ fuzzy filtering technique for non‐linear sampled‐data systems that are represented on the basis of the Takagi–Sugeno fuzzy model. To improve the performance of the fuzzy filter, an imperfect premise matching condition is considered. An error system between the non‐linear system and the fuzzy filter is constructed. In addition, sufficient conditions for showing asymptotic stability and guaranteeing H ∞ disturbance attenuation performance are proposed in a Lyapunov sense and derived in terms of linear matrix inequalities. Finally, the feasibility of the proposed technique is demonstrated using two simulation examples.