Non-fragile robust finite-time H ∞ control for nonlinear stochastic itô systems using neural network

• DOI: 10.1007/s12555-012-0502-6
• Publication Date: 2012-09-30T21:55:12Z
• Authors: Zhiguo Yan; Guoshan Zhang; Jiankui Wang
• Keywords: Differential inclusion; Matrix (chemical analysis); Linear matrix inequality; Representation

This paper deals with the problem of non-fragile robust finite-time H∞ control for a class of uncertain nonlinear stochastic Ito systems via neural network. First, applying multi-layer feedback neural networks, the nonlinearity is approximated by linear differential inclusion (LDI) under statespace representation. Then, a sufficient condition is proposed for the existence of non-fragile state feedback finite-time H∞ controller in terms of matrix inequalities. Furthermore, the problem of nonfragile robust finite-time H∞ control is reduced to the optimization problem involving linear matrix inequalities (LMIs), and the detailed solving algorithm is given for the restricted LMIs. Finally, an example is given to illustrate the effectiveness of the proposed method.