Distributed control over networks using smoothing techniques

Abstract

In this paper we propose two dual decomposition methods based on smoothing techniques, called here the proximal center method and the interior-point Lagrangian method, to solve distributively separable convex problems. We show that some relevant centralized control problems can be recast as a separable convex problem for which our dual methods can be applied. The new dual optimization methods are suitable for application to distributed control since they are highly parallelizable, each subsystem uses local information and the coordination between the local controllers is performed via the Lagrange multipliers corresponding to the coupled dynamics or constraints. © 2009 Springer Berlin Heidelberg.