Title :
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
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.;
Journal_Title :
Neural Networks and Learning Systems, IEEE Transactions on
DOI :
10.1109/TNNLS.2015.2460239
