H∞ fuzzy estimation for a class of nonlinear discrete-time dynamic systems

This paper studies fuzzy filtering design for state estimation of nonlinear discrete-time systems with bounded but unknown disturbances. First, the Takagi and Sugeno fuzzy model is proposed to represent a nonlinear system. Next, using a linear matrix inequality (LMI) approach, the fuzzy filtering problems are characterized in terms of a linear matrix inequality problem (LMIP). The LMIP can be efficiently solved using convex optimization techniques. Simulation examples are given to illustrate the design procedure and the applicability of the proposed method. The results indicate that the proposed method is suitable for practical applications.