A distributed optimization-based approach for hierarchical model   predictive control of large-scale systems with coupled dynamics and   constraints
  We present a hierarchical model predictive control approach for large-scale systems based on dual decomposition. The proposed scheme allows coupling in both dynamics and constraints between the subsystems and generates a primal feasible solution within a finite number of iterations, using primal averaging and a constraint tightening approach. The primal update is performed in a distributed way and does not require exact solutions, while the dual problem uses an approximate subgradient method. Stability of the scheme is established using bounded suboptimality. 
Minh Dang Doan, Tam\'as Keviczky, and Bart De Schutter
math.OC cs.MA cs.SY