ROBUST ESTIMATION FOR DISCRETE TIME-VARYING SYSTEMS WITH LIMITED COMMUNICATION CAPACITY

In this paper, we consider the state estimation problem for linear discrete time-varying systems subject to limited communication capacity (e.g., measurement quantization, random transmission delay and data-packet dropouts). Based on transforming the three communication limitations into the system with norm-bounded uncertainties and stochastic matrices, we design a robust filter such that, for all the communication limitations, the error state of the filtering process is mean square bounded. An upper bound on the variance of the state estimation error is first found, and then, a robust filter is derived by minimizing the prescribed upper bound in the sense of the matrix norm. It is shown that the desired filter can be obtained in terms of the solutions to two Riccati-like difference equations which also provide a recursive algorithm suitable for online computation. A simulation example is presented to demonstrate the effectiveness and applicability of the proposed algorithm.