RobustH∞output feedback design for networked control systems with partially known delay probabilities

This article develops a predictive robustH(infinity)static output feedback control approach for networked control systems where random network-induced delays in both forward and feedback communication channels are modeled as two mutually uncorrelated Markov chains. By making use of the system augmentation method, the closed-loop system is formulated as a singular Markovian jump system with two modes, wherein the transition probability matrices of the underlying Markov chains are considered to be partially accessible. Necessary and sufficient conditions for the stochastic admissibility and robustH(infinity)performance of the closed-loop system are given under the assumption of partially known transition probability matrices. A linear matrix inequality condition is proposed to determine the two-mode-dependent static output feedback controller gains to compensate for the random network-induced delays efficiently and provide the desired control performance. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed approach.