Quantized control for nonhomogeneous Markovian jump T-S fuzzy systems with missing measurements

In this paper, in terms of the T-S fuzzy technique, the quantization control designs are resolved for a class of nonhomogeneous Markov jump systems (MJSs) with partially unknown transition probabilities. Different from the previous research, the transition probabilities are time-variant and not known exactly in the MJSs. Particularly in a network environment, it is considered that the effects of data packet dropouts and the occurrence of signal quantization simultaneously emerge in the closed-loop circuit. Furthermore, based on a fuzzy Lyapunov function and a set of linear matrix inequalities, one can achieve the desired H∞ performance and the sufficient conditions such that the corresponding closed-loop system is stochastically stable. By the cone complementarity linearisation (CCL) procedure, a sequential minimization problem is tackled efficiently to gain the solutions of the dynamic output feedback controller (DOFC). Finally, the validity of the suggested technique is showed via a simulation example.