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Robust guaranteed cost control for time‐delay fractional‐order neural networks systems
Author(s) -
Thuan Mai Viet,
Huong Dinh Cong
Publication year - 2019
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2497
Subject(s) - control theory (sociology) , stability theory , artificial neural network , controller (irrigation) , mathematics , bilinear interpolation , computer science , control (management) , state (computer science) , order (exchange) , lyapunov function , mathematical optimization , nonlinear system , algorithm , artificial intelligence , statistics , physics , finance , quantum mechanics , agronomy , economics , biology
Summary In this paper, we investigate the problem of guaranteed cost control of uncertain fractional‐order neural networks systems with time delays. By employing the Lyapunov‐Razumikhin theorem, a sufficient condition for designing a state‐feedback controller which makes the closed‐loop system asymptotically stable and guarantees an adequate cost level of performance is derived in terms of bilinear matrix inequalities. Two numerical examples are given to show the effectiveness of the obtained results.