Sliding mode control problem of a class of Ito^ type partial differential equations with delay is probed. The variable structure controller is designed. The existence of motion of sliding mode is shown. And the character of invariance of sliding control system about uncertainty on the sliding switching surface and stability are analyzed.
So far, the Lyapunov direct method is still the most effective technique in the study of stability for ordinary differential equations and stochastic differential equations. Due to the shortage of the corresponding It6 formula, this useful method has not been popularized in stochastic partial differential equations. The aim of this work is to try to extend the Lyapunov direct method to the It6 stochastic reaction diffusion systems and to establish the corresponding Lyapunov stability theory, including stability in probablity, asymptotic stability in probablity, and exponential stability in mean square. As the application of the obtained theorems, this paper addresses the stability of the Hopfield neural network and points out that the main results ob- tained by Holden Helge and Liao Xiaoxin et al. can be all regarded as the corollaries of the theorems presented in this paper.
LUO QiDENG FeiQiMAO XueRongBAO JunDongZHANG YuTian
This work is devoted to the discussion of stochastic reaction diffusion equations and some new theorems on Lagrange stability in mean square of the solution are established via Lyapunov method which is nothing to be done in the past.
Luo Qi (Dept. of Inform, and Communication, Nanjing University of Information Science and Technology, Nanjing 210044) Bao Jundong (College, of Math. Science, Inner Mongolia Normal University, Huhehaott 010022) Zhang Yutian (College of Science, Wuhan University of Sci. and Technology, Wuhan 430081)
