Reference:
D. Doan,
T. Keviczky,
I. Necoara,
M. Diehl, and
B. De Schutter,
"A distributed version of Han's method for DMPC of dynamically coupled
systems with coupled constraints," Proceedings of the 1st IFAC
Workshop on Estimation and Control of Networked Systems (NecSys
2009), Venice, Italy, pp. 240-245, Sept. 2009.
Abstract:
Most of the literature on Distributed Model Predictive Control (DMPC)
for dynamically coupled linear systems typically focuses on situations
where coupling constraints between subsystems are absent. In order to
address the presence of convex coupling constraints, we present a
distributed version of Han's parallel algorithm for a class of convex
programs. The algorithm we propose relies on local iterative updates
only, instead of using system-wide information exchange as in Han's
original algorithm. The new algorithm is then used to develop a new
distributed MPC method that is applicable to sparsely coupled linear
dynamical systems with coupled linear constraints. Convergence to the
global optimum, recursive feasibility, and stability can be
established using only local communications between the subsystems.