Approximation property of T-S fuzzy singular systems
T-S模糊广义系统的逼近性

This article focuses on the approximation problem of T-S fuzzy singular systems. An approximation theorem of T-S fuzzy singular systems is proposed. It demonstrates that T-S fuzzy singular systems could approximate to a wide class of nonlinear singular systems with arbitrarily high accuracy. The MISO (multi-input single-output) situation is extended to MIMO (multi-input multi-output) situation. Based on this approximation theorem and using neural network method, the model of T-S fuzzy singular systems can be constructed along with its learning algorithm. Two neural network training strategies are also proposed and their advantages and disadvantages are analyzed respectively. Finally, a numerical example is given to illustrate the validity of the algorithms.