Control energy of lattice graphs. Klickstein, I. & Sorrentino, F. In Decision and Control (CDC), 2018 IEEE 57th Annual Conference on, 2018. IEEE. abstract bibtex The control of complex networks has generated a lot of interest in a variety of fields from traffic management to neural systems. A commonly used metric to compare two particular control strategies that accomplish the same task is the control energy, the integral of the sum of squares of all control inputs. The minimum control energy problem determines the control input that lower bounds all other control inputs with respect to their control energies. Here, we focus on the infinite lattice graph with linear dynamics and analytically derive the expression for the minimum control energy in terms of the modified Bessel function. We then demonstrate that the control energy of the infinite lattice graph accurately predicts the control energy of finite lattice graphs.
@inproceedings{klickstein2018control,
title={Control energy of lattice graphs},
author={Klickstein, Isaac and Sorrentino, Francesco},
booktitle={Decision and Control (CDC), 2018 IEEE 57th Annual Conference on},
year={2018},
organization={IEEE},
abstract={The control of complex networks has generated a lot of interest in a variety of fields from traffic management to neural systems. A commonly used metric to compare two particular control strategies that accomplish the same task is the control energy, the integral of the sum of squares of all control inputs. The minimum control energy problem determines the control input that lower bounds all other control inputs with respect to their control energies. Here, we focus on the infinite lattice graph with linear dynamics and analytically derive the expression for the minimum control energy in terms of the modified Bessel function. We then demonstrate that the control energy of the infinite lattice graph accurately predicts the control energy of finite lattice graphs.}
}
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