Distributed model predictive control via decomposition-coordination techniques and the use of an augmented Lagrangian

Didier Georges (1)

1 LAG - Laboratoire d'automatique de Grenoble

This paper is devoted to distributed nonlinear predictive control design through the use of both an augmented Lagrangian formulation and price - decomposition - coordination. We show how Lagrangian relaxation can be used to design a distributed MPC scheme, which allows dramatic reduction of the computational requirements for solving large-scale nonlinear MPC problems due to computation parallelism. The effectiveness of this approach is demonstrated for the so-called Load Frequency Control of power systems.

Mots clés: Distributed model predictive control; interconnected systems; decomposition-coordination; augmented Lagrangian

Domaines: Automatique / Robotique

Didier Georges. Distributed model predictive control via decomposition-coordination techniques and the use of an augmented Lagrangian. Oct 2006, no page numbers. ⟨hal-00108368⟩