Open AccessRobust observer synthesis for the uncertain large‐scale T–S fuzzy system
Author(s) -
Vu VanPhong,
Wang WenJune
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.2018.5191
Subject(s) - control theory (sociology) , observer (physics) , fuzzy logic , mathematics , fuzzy control system , lyapunov function , linear matrix inequality , robust control , set (abstract data type) , computer science , scale (ratio) , state observer , robustness (evolution) , mathematical optimization , control system , nonlinear system , control (management) , engineering , artificial intelligence , physics , quantum mechanics , electrical engineering , biochemistry , chemistry , gene , programming language
This work studies a new method to synthesise a robust observer to estimate the immeasurable state variables for an uncertain large‐scale Takagi–Sugeno (T–S) fuzzy system, which has not been considered in the previous studies. This system consists of a set of T–S fuzzy subsystems that are interconnected, but these systems have certain uncertainties. An observer relying on the unknown input method is synthesised such that not only the unknown states are estimated but also the effects of the uncertainties are eliminated completely, even though the upper bounds of the uncertainties are not known. The conditions to design the observer are obtained in the main theorems by employing Lyapunov methodology, S‐procedure, and linear matrix inequalities technique. Finally, the illustrative examples are provided to illustrate the advantages and success of the proposed method.