Friday,
October 6, 2017, 3pm

Location: Planetary Hall Room 126

**Francesco
Sorrentino**

Department of Mechanical Engineering

University of New Mexico

**Optimal Control of Networks: Energy
Scaling and Open Challenges**

__Abstract__

Recent years have witnessed increased interest from the scientific community
regarding the control of complex dynamical networks. Some common types of
networks examined throughout the literature are power grids, communication
networks, gene regulatory networks, neuronal systems, food webs, and social
systems. Optimal control studies strategies to control a system that minimize a
cost function, for example the *energy* that is required by the control
action.

We show that by controlling the states of a subset of the nodes of a network, rather than the state of every node, the required energy to control a portion of the network can be reduced substantially. The energy requirements exponentially decay with the number of target nodes, suggesting that large networks can be controlled by a relatively small number of inputs, as long as the target set is appropriately sized.

An important observation is that the minimum energy solution of the control problem for a linear system produces a control trajectory that is nonlocal. However, when the network dynamics is linearized, the linearization is only valid in a local region of the state space and hence the question arises whether optimal control can be used. We provide a solution to this problem by determining the region of state space where the trajectory does remain local and so minimum energy control can still be applied to linearized approximations of nonlinear systems. We apply our results to develop an algorithm that determines a piecewise open-loop control signal for nonlinear systems. Applications include controlling power grid dynamics and the regulatory dynamics of the intracellular circadian clock.

__References__

Shirin, Klickstein,
Sorrentino, Chaos 27, 041103 (2017).

Klickstein, Shirin, Sorrentino, Nature Communications
8, 15145 (2017).