Decentralized sampled-data H∞H∞ fuzzy filter for nonlinear large-scale systems

This paper presents a decentralized sampled-data H∞H∞ fuzzy filter design method for nonlinear large-scale systems which are represented by a Takagi–Sugeno (T–S) fuzzy model. Based on the T–S fuzzy model, the error system between the nonlinear large-scale system and the filter is obtained. The discretization process of the error system is accomplished with the exact discrete-time approach to eliminate the exact-approximate mismatch. By using the discrete-time Lyapunov sense, the sufficient condition of the asymptotic stability for the error system is given and a prescribed level of the H∞H∞ norm is ensured to guarantee the H∞H∞ fuzzy filter performance. Finally, numerical examples are given to show the effectiveness of the proposed methods.