Sparsity-promoting optimal control of consensus and synchronization networks

We study a class of optimal control problems that are encountered in consensus and synchronization networks. These are characterized by structural constraints that arise from the lack of the absolute measurements for a part of the state vector. In order to deal with these constraints, we introduce a coordinate transformation to eliminate the average mode and assure stabilizability and detectability of the remaining modes. To design networks with low communication requirements, we seek solutions to the ℓ₁ regularized version of the standard ℋ₂ optimal control problem. Such solutions trade off network performance and sparsity of the controller. We also identify a class of optimal control problems that can be cast as semidefinite programs. Examples from power systems and consensus networks are provided to illustrate our developments.