Jorge Cortés
Professor
Cymer Corporation Endowed Chair
Singularly perturbed algorithms for dynamic average consensus
S. S. Kia, J. Cortés, S. Martínez
Proceedings of the European Control Conference, Zürich, Switzerland, 2013, pp. 1758-1763
Abstract
This paper proposes two continuous-time dynamic average consensus
algorithms for networks with strongly connected and weight-balanced
interaction topologies. The proposed algorithms, termed
1st-Order-Input Dynamic Consensus (FOI-DC) and 2nd-Order-Input
Dynamic Consensus (SOI-DC), respectively, allow agents to track the
average of their dynamic inputs within an O(\epsilon)-neighborhood
with a pre-specified rate. The only requirement on the set of
reference inputs is having continuous bounded derivatives, up to
second order for FOI-DC and up to third order for SOI-DC. The
correctness analysis of the algorithms relies on singular
perturbation theory for non-autonomous dynamical systems. When
dynamic inputs are offset from one another by static values, we show
that SOI-DC converges to the exact dynamic average with no
steady-state error. Simulations illustrate our results.
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Mechanical and Aerospace Engineering,
University of California, San Diego
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