Distributed State Estimation for a Class of Jointly Observable Nonlinear Systems

State estimation for a class of nonlinear systems using a network of distributed observers is dealt with in this paper. We propose a network of observers, each of which has its own local measurements which may not be sufficient for observability of the system, while the joint measurements of the sensors in the network guarantees the observability. We derive sufficient conditions on the proposed observers such that the estimated states of each observer asymptotically converge to the states of the system using local measurements and the estimates of a subset of observers in its neighborhood. Accordingly, it is assumed that each observer has access to the estimates of its neighbors via a communication network. The main problem of existing distributed state estimation strategies in the literature is their limitation to linear systems or to nonlinear systems with observable nonlinearities (by considering nonlinearities as states to be estimated). However, based on the proposed strategy, distributed state estimation of a more general class of nonlinear systems can be devised. A numerical example is provided to evaluate the accuracy of the obtained results.The final publication is available at sciencedirect.com via https://doi.org/10.1016/j.ifacol.2020.12.1108. G. Yang, H. Rezaee, and T. Parisini, Distributed State Estimation for a Class of Jointly Observable Nonlinear Systems, IFAC-PapersOnLine, Volume 53, Issue 2, 2020, Pages 5045-5050, doi: 10.1016/j.ifacol.2020.12.1108