A DMPC method is proposed that solves the dual problem via inexact primal-dual gradient optimization with Laplacian consensus and uses contraction theory to guarantee convergence, recursive feasibility, and stability under premature termination.
On the convergence time of dual sub gradient methods for strongly convex programs,
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Distributed Model Predictive Control Under Inexact Primal-Dual Gradient Optimization Based on Contraction Analysis
A DMPC method is proposed that solves the dual problem via inexact primal-dual gradient optimization with Laplacian consensus and uses contraction theory to guarantee convergence, recursive feasibility, and stability under premature termination.