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Center for Nonlinear Studies |
We consider the problem of defining an optimal strategy to control a dynamical complex network, optimal in terms of a general cost function. Here we show that by controlling a network's output rather than the state of every node, the required energy to control the network can be reduced substantially. In particular, by only targeting a subset of the nodes of the network, the energy requirements exponentially decay. We also show that the minimum energy well approximates the energy required for a large family of cost objectives so that the benefits of target control extend beyond the minimum energy control scheme considered in the literature. We validate our conclusions in model and real networks to arrive at an energy scaling law to better design control objectives regardless of system size, energy restrictions, state restrictions, driver node choices and target node choices.