Fuzzy hyperbolic neural network model and its application in H ∞ filter design

Abstract

This paper studies H∞ filter based on a new fuzzy neural model for signal estimation of nonlinear continuous-time systems with time delays. First, a new fuzzy neural model, called fuzzy hyperbolic neural network model (FHNNM), is developed. FHNNM is a combination of the special fuzzy model and the modified BP neural network. The main advantages of using the FHNNM over traditional fuzzy neural network are that explicit expression of expert's experience and global analytical description. In addition, by contrast with fuzzy neural network based T-S fuzzy model, no premise structure identification is need and no completeness design of premise variables space is need. Next, we design a stable H∞ filter based on the FHNNM using linear matrix inequality (LMI) method. Simulation example is provided to illustrate the design procedure of the proposed method. © 2008 Springer-Verlag Berlin Heidelberg.