H-infinite State Estimation for Takagi-Sugeno Fuzzy Delayed Hopfield Neural Networks

Abstract

This paper presents a H-infinite state estimator for Takagi-Sugeno fuzzy delayed Hopfield neural networks. Based on Lyapunov-Krasovskii stability approach, a delay-dependent criterion is proposed to ensure that the resulting estimation error system is asymptotically stable with a guaranteed H performance. The proposed H state estimator can be realized by solving a linear matrix inequality (LMI) problem. An illustrative numerical example is given to verify the effectiveness of the proposed H-infinite state estimator.

Keywords

• H-infinite state estimation
• Takagi-Sugeno fuzzy Hopfield neural networks
• linear matrix inequality