Interval T-S fuzzy model and its application to identification of nonlinear interval dynamic system based on interval data
Zhengguang Xu, Changping Sun · 2009
In this paper, a new fuzzy system model structure-interval T-S fuzzy model (ITSFM) is proposed. Inspired from interval regression analysis, the interval arithmetic is incorporated with classical T-S fuzzy model and the parameters in consequent part of the ITSFM model become to be intervals. Thus, the outputs of the proposed ITSFM are intervals. In addition, we define fuzzy interval set, center membership function and radius membership function for intervals and an arithmetical operation between a constant interval and a general real vector. Then the proposed ITSFM is applied to identification of nonlinear interval dynamic system based on the measured interval data. Experimental results are then presented that indicate the validity and applicability of the proposed ITSFM.