Open AccessNon‐fragile sampled‐data guaranteed cost control for bio‐economic fuzzy singular Markovian jump systems
Author(s) -
Sakthivel R.,
Kanagaraj R.,
Wang C.,
Selvaraj P.,
Anthoni S.M.
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.2018.5285
Subject(s) - control theory (sociology) , linear matrix inequality , mathematics , controller (irrigation) , fuzzy logic , impulse (physics) , fuzzy control system , bounded function , jump , control (management) , computer science , mathematical optimization , mathematical analysis , physics , quantum mechanics , artificial intelligence , agronomy , biology
This study investigates the non‐fragile sampled‐data guaranteed cost control problem for a bio‐economic singular Markovian jump system that is represented by the Takagi–Sugeno fuzzy model. The main intention of this study is to design a non‐fragile sampled‐data controller for the considered model to handle the issue of tax fluctuations by means of showing that the closed‐loop system is regular, impulse free and stochastically finite‐time bounded. Sampled‐data controller is the one where the continuous system is controlled by the digital control algorithms. By introducing a proper Lyapunov–Krasovskii functional and using linear matrix inequality (LMI) approach, a new set of criteria is obtained in terms of LMIs for achieving the required result. More precisely, by solving LMIs, an upper bound for the cost function can be obtained. Finally, a simulation result is given to illustrate the effectiveness of the proposed control design.