Distributed State Estimation for Multi-agent Systems Under Consensus Control

Distributed state estimation and consensus control for linear time-invariant multi-agent systems under strongly connected directed graph are addressed in this paper. The distributed output tracking algorithm and the local state estimator are designed for each agent to estimate the output and state of the entire multi-agent system, despite having access only to local output measurements that are insufficient to directly reconstruct the entire state. The consensus control protocol is further designed based on each agent’s own entire state estimation. Neither distributed state estimation nor consensus control protocol design requires state information from neighboring agents, eliminating the transmission of the values of state estimations during the whole process. The theoretical analysis demonstrates that the realization of distributed output tracking and state estimation. Moreover, all agents achieve consensus. Finally, numerical simulations are worked out to show the effectiveness of the proposed algorithm.