Fuzzy observer and fuzzy controller design for a class of uncertain non‐linear systems
Author(s) -
Shuli Guo,
Lina Han,
Xianjia Feng
Publication year - 2016
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.2015.0268
Subject(s) - control theory (sociology) , observer (physics) , lyapunov function , mathematics , fuzzy logic , fuzzy control system , controller (irrigation) , separation principle , state observer , computer science , nonlinear system , control (management) , artificial intelligence , physics , quantum mechanics , agronomy , biology
In this study, a fuzzy state observer and a fuzzy controller are developed for a class of uncertain non‐linear systems, which are represented through a set assumptions of matrix inequalities. Many original investigations and results are obtained. First, by constructing a class of Lyapunov functions and the introduced matrix inequalities tools, the adaptive observer laws including new Ricatti equations, two differentiators and many solvability conditions about the obtained Ricatti equations are presented. Second, based on another class of Lyapunov functions and the same matrix inequalities tools, the proposed controllers are designed to guarantee the stability of the overall closed‐loop systems, and many solvability conditions on the proposed controllers are analysed too. Finally, numerical simulations on the single‐input single‐output magnetic levitation systems show the effectiveness of these approaches. The above work allows to provide further applications on the proposed observer and controller designs without resorting to universal fuzzy approximation.
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