Title of article :
An LMI approach for global robust dissipativity analysis of T–S fuzzy neural networks with interval time-varying delays
Author/Authors :
S. Muralisankar، نويسنده , , S. G. Gopalakrishnan، نويسنده , , N. and Balasubramaniam، نويسنده , , P.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Abstract :
Takagi–Sugeno (T–S) fuzzy models are often used to represent complex nonlinear systems by means of fuzzy sets and fuzzy reasoning applied to a set of linear sub-models. In this paper, the global robust dissipativity of T–S fuzzy neural networks with interval time-varying delays are investigated. By constructing a proper Lyapunov–Krasovskii functional and using linear matrix inequality (LMI) technique, delay-dependent criteria for checking the global dissipativity and global exponential dissipativity of fuzzy neural networks have been derived in terms of LMI, which can be solved numerically using LMI toolbox in MATLAB. Finally, numerical examples are given to illustrate the effectiveness of the theoretical results.
Keywords :
NEURAL NETWORKS , T–S fuzzy model , Linear matrix inequality , Global dissipativity , Time-varying delays
Journal title :
Expert Systems with Applications
Journal title :
Expert Systems with Applications