Finite-Time Stabilizability and Instabilizability of Delayed Memristive Neural Networks With Nonlinear Discontinuous Controller

Author

Leimin Wang ; Yi Shen

Author_Institution

Sch. of Autom., Huazhong Univ. of Sci. & Technol., Wuhan, China

Volume

26

Issue

11

fYear

2015

Firstpage

2914

Lastpage

2924

Abstract

This paper is concerned about the finite-time stabilizability and instabilizability for a class of delayed memristive neural networks (DMNNs). Through the design of a new nonlinear controller, algebraic criteria based on M-matrix are established for the finite-time stabilizability of DMNNs, and the upper bound of the settling time for stabilization is estimated. In addition, finite-time instabilizability algebraic criteria are also established by choosing different parameters of the same nonlinear controller. The effectiveness and the superiority of the obtained results are supported by numerical simulations.

Keywords

control system synthesis; delay systems; matrix algebra; neurocontrollers; nonlinear control systems; sampled data systems; stability; DMNN; M-matrix; delayed memristive neural networks; finite-time instabilizability algebraic criteria; finite-time stabilizability; nonlinear controller design; nonlinear controller parameters; nonlinear discontinuous controller; numerical simulations; settling time; upper bound; Asymptotic stability; Bismuth; Control systems; Delays; Memristors; Neural networks; Stability criteria; Delayed memristive neural networks (DMNNs); finite-time instabilizability; finite-time stabilizability; nonlinear controller; settling time; settling time.;

fLanguage

English

Journal_Title

Neural Networks and Learning Systems, IEEE Transactions on

Publisher

ieee

ISSN

2162-237X

Type

jour

DOI

10.1109/TNNLS.2015.2460239

Filename

7185434