  In this article, we focus on the cooperative state estimation problem of a
multi-agent system. Each agent is equipped with absolute and relative
measurements. The purpose of this research is to make each agent generate its
own state estimation with only local measurement information and local
communication with neighborhood agents using Set Membership Filter(SMF). To
handle this problem, we analyzed centralized SMF framework as a benchmark of
distributed SMF and propose a finite-horizon method called OIT-Inspired
centralized constrained zonotopic algorithm. Moreover, we put forward a
distributed Set Membership Filtering(SMFing) framework and develop a
distributed constained zonotopic algorithm. Finally, simulation verified our
theoretical results, that our proposed algorithms can effectively estimate the
state of each agent.
