Stochastic stabilization of networked control systems with partly unknown Markovian transition probabilities

The mean square exponentially stabilization problem of the networked control system with the Markovian network-induced time delay and data packet dropout characteristics was studied. The closed loop networked control system was modeled as a discrete-time switching system of which the switching sequence was governed by a Markov chain with partly unknown transition probabilities. The sufficient conditions for mean square exponentially stabilization of the closed loop system was given by using the Markov theory and the Average Dwell Time (ADT) method. Then the state feedback controller is obtained by solving a series of linear matrix inequalities (LMIs). Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed result.