Robust H∞ output feedback control of discrete-time networked systems with adaptive quantizers

Quantizers with coarser quantization densities are helpful in reducing network congestion. In this paper, we investigate the problem of designing a robust H_∞ output feedback controller for discrete-time networked systems with an adaptive quantization density or limited information. A Markov process is used to model the randomness of the network load condition and a Bernoulli process is used to model packet dropouts. A stability criterion is developed by using Lyapunov-Krasovskii functional and sufficient conditions for the existence of a dynamic quantized output feedback controller are given in terms of Bilinear Matrix Inequalities(BMIs). An iterative algorithm is suggested to obtain quasi-convex Linear Matrix Inequalities (LMIs) from BMIs.