This paper studies a challenging issue introduced in a recent survey, namely
designing a distributed event-based scheme to solve the dynamic average
consensus (DAC) problem. First, a robust adaptive distributed event-based DAC
algorithm is designed without imposing specific initialization criteria to
perform estimation task under intermittent communication. Second, a novel
adaptive distributed dynamic event-triggered mechanism is proposed to determine
the triggering time when neighboring agents broadcast information to each
other. Compared to the existing event-triggered mechanisms, the novelty of the
proposed dynamic event-triggered mechanism lies in that it guarantees the
existence of a positive and uniform minimum inter-event interval without
sacrificing any accuracy of the estimation, which is much more practical than
only ensuring the exclusion of the Zeno behavior or the boundedness of the
estimation error. Third, a composite adaptive law is developed to update the
adaptive gain employed in the distributed event-based DAC algorithm and dynamic
event-triggered mechanism. Using the composite adaptive update law, the
distributed event-based solution proposed in our work is implemented without
requiring any global information. Finally, numerical simulations are provided
to illustrate the effectiveness of the theoretical results.Comment: 9 pages, 8 figure