  In this paper, network of agents with identical dynamics is considered. The
agents are assumed to be fed by self and neighboring output measurements, while
the states are not available for measuring. Viewing distributed estimation as
dual to the distributed LQR problem, a distributed observer is proposed by
exploiting two complementary distributed LQR methods. The first consists of a
bottom-up approach in which optimal interactions between self-stabilizing
agents are defined so as to minimize an upper bound of the global LQR
criterion. In the second (top-down) approach, the centralized optimal LQR
controller is approximated by a distributed control scheme whose stability is
guaranteed by the stability margins of LQR control. In this paper, distributed
observer which minimizes an upper bound of a deterministic performance
criterion, is proposed by solving a dual LQR problem using bottom-up approach.
The cost function is defined by considering minimum-energy estimation theory
where the weighting matrices have deterministic interpretation. The presented
results are useful for designing optimal or near-optimal distributed
control/estimation schemes.

Systems and Control;Systems and Control