Robust optimal estimation over networks: Application to battery state of charge estimation

In this paper, we provide a general framework for robust optimal estimation over a lossy and delayed network. A threshold principle is introduced to integrate network-induced uncertainties into packet losses, which are modeled with a Bernoulli process. Based on stability conditions derived from two Riccati equations, we show the existence of critical observation arrival probabilities below which the optimal estimator stochastically fails to converge. Moreover, the result is extended to a real system with variable process disturbance, which has an indicator for its admissible bound in terms of a given restriction of estimation accuracy. The proposed method is experimented on a specific automobile application, the battery state of charge estimation. Copyright (C) 2015 John Wiley & Sons, Ltd.