Robust finite time stabilization analysis for uncertain neural networks with leakage delay and probabilistic time-varying delays
Muthukumar, P, Subramanian, K and Lakshmanan, S 2016, Robust finite time stabilization analysis for uncertain neural networks with leakage delay and probabilistic time-varying delays, Journal of the Franklin Institute, vol. 353, no. 16, pp. 4091-4113, doi: 10.1016/j.jfranklin.2016.07.006.
Attached Files
Name
Description
MIMEType
Size
Downloads
Title
Robust finite time stabilization analysis for uncertain neural networks with leakage delay and probabilistic time-varying delays
This paper investigates the problem of robust finite time stabilization for a uncertain neural networks with leakage delay and probabilistic time-varying delays. By introducing a stochastic variable which satisfies Bernoulli distribution, the information of probabilistic time-varying delay is equivalently transformed into the deterministic time-varying delay with stochastic parameters. The main objective of this paper is to design a memoryless state feedback control such that the resulting proposed system is robustly finite time stable with admissible uncertainties. Based on a suitable Lyapunov–Krasovskii functional, model transformation technique and Wirtinger-based double integral inequality, the general framework is obtained in terms of linear matrix inequalities to determine the finite time stability and to achieve the control design. Finally, three numerical examples are presented to validate the effectiveness and less conservatism of the proposed method.
Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.