Distributed State Estimation Using Asynchronous Sampled-data

Abstract

This report is concerned with a state observer using asynchronously sampled outputs. In networked systems, measured outputs may be sampled asynchronously, or synchronously sampled data may not be transmitted simultaneously due to transmission delays or data collisions in the communication network. In this report, we develop a distributed state observer using asynchronously sampled data. First, we propose a distributed observer consisting of Luenburger-type sub-predictors with sampled-data couplings between the sub-predictors. Next, deriving the estimation error dynamics, we derive a sufficient condition for the origin of the error dynamics to be asymptotically stable. After that, we propose a design method for the observer gain matrix and the coupling gain matrix for each sub-predictor. These conditions are derived in the form of linear matrix inequalities. The validity of the proposed estimation scheme is illustrated by a numerical example.