Steering the dynamics by controlling the temporal interaction network
The paper proposes a method using nonlinear optimal control to steer coupled dynamical systems by tuning their temporal interaction network (coupling matrix). It uses an adjoint method to find the gradient of a cost function, allowing researchers to control how nodes' states evolve. Results show this framework can successfully steer heterogeneous nodes toward common or distinct target trajectories.