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arXiv · 1810.08287

Performance Improvement in Noisy Linear Consensus Networks with Time-Delay

Yaser Ghaedsharaf·Milad Siami·Christoforos Somarakis·Nader Motee
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Abstract

We analyze performance of a class of time-delay first-order consensus networks from a graph topological perspective and present methods to improve it. The performance is measured by network's square of H-2 norm and it is shown that it is a convex function of Laplacian eigenvalues and the coupling weights of the underlying graph of the network. First, we propose a tight convex, but simple, approximation of the performance measure in order to achieve lower complexity in our design problems by eliminating the need for eigen-decomposition. The effect of time-delay reincarnates itself in the form of non-monotonicity, which results in nonintuitive behaviors of the performance as a function of graph topology. Next, we present three methods to improve the performance by growing, re-weighting, or sparsifying the underlying graph of the network. It is shown that our suggested algorithms provide near-optimal solutions with lower complexity with respect to existing methods in literature.

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BibTeXRIS

Yaser Ghaedsharaf, Milad Siami, Christoforos Somarakis, Nader Motee. 2018-10-18. Performance Improvement in Noisy Linear Consensus Networks with Time-Delay. https://arxiv.org/abs/1810.08287

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