New stability and stabilization criteria for fuzzy neural networks with various activation functions

作者：Mathiyalagan K; Sakthivel R^*; Anthoni S Marshal

来源：Physica Scripta, 2011, 84(1): 015007.

DOI：10.1088/0031-8949/84/01/015007

In this paper, the stability analysis and control design of Takagi-Sugeno (TS) fuzzy neural networks with various activation functions and continuously distributed time delays are addressed. By implementing the delay-fractioning technique together with the linear matrix inequality (LMI) approach, a new set of sufficient conditions is derived in terms of linear matrix inequalities, which ensure the stability of the considered fuzzy neural networks. Further, based on the above-mentioned techniques, a control law with an appropriate gain control matrix is derived to achieve stabilization of the fuzzy neural networks. In addition, the results are extended to the study of the stability and stabilization results for TS fuzzy uncertain neural networks with parameter uncertainties. The stabilization criteria are obtained in terms LMIs and hence the gain control matrix can be easily determined by the MATLAB LMI control toolbox. Two numerical examples with simulation results are given to illustrate the effectiveness of the obtained result.

• 出版日期2011-7