A Distributed Observer Design for Linear Systems Using Asynchronous Sampled Data

Abstract

This paper concerns a distributed estimation problem for large-scale systems with data acquired by sensor networks. Since each sensor node in a sensor network acquires the measurements at its timing, the measured data of all the sensors could be asynchronous and aperiodic sampled data. This paper develop a distributed observer for linear time-invariant (LTI) systems with asynchronously sampled data to estimate the whole state from such data. After deriving a stability condition for the estimation error dynamics, we show that the maximum allowable sampling interval and appropriate observer gain matrices, such that the estimation error converges asymptotically to zero, can be computed by solving the derived linear matrix inequality condition. The obtained observer can estimate the whole state of the systems without any clock-synchronization mechanism.