Mean Square Stabilization for Sampled-Data T-S Fuzzy Systems With Random Packet Dropout

This paper investigates the problem of mean square stabilization for sampled-data Takagi-Sugeno (T-S) fuzzy networked control systems with random packet dropouts. The packet dropout process is modeled as a discrete-time Markovian chain with complete or incomplete accessible transition probability matrix. Based on the Lyapunov function approach, sufficient conditions are derived for the mean square stability. The corresponding sampled-data fuzzy controller design algorithm formulated in terms of linear matrix inequalities is also given based upon the stability conditions. The numerical examples and simulations are provided to illustrate the usefulness of the developed theory.