Quantized robust filtering of semi-Markov jump systems with random measurement data dropouts

This paper addresses the quantized robust filtering problem for a class of discrete-time semi-Markov jump systems with random measurement data dropouts. A random variable obeying the Bernoulli distribution is introduced to describe the data loss phenomenon. Considering the limited network communication, the measurement output is transmitted to the filter through a logarithmic quantizer. Based on this, a Lyapunov function is constructed that depends on both the mode and residence time. The conditions for the existence of the mode-dependent quantization filter are obtained, and the estimation error is guaranteed to be mean-square stable. The effectiveness of the proposed quantized filtering strategy is verified by an example.