  Various efforts have been devoted to developing stabilizing distributed Model
Predictive Control (MPC) schemes for tracking piecewise constant references. In
these schemes, terminal sets are usually computed offline and used in the MPC
online phase to guarantee recursive feasibility and asymptotic stability.
Maximal invariant terminal sets do not necessarily respect the distributed
structure of the network, hindering the distributed implementation of the
controller. On the other hand, ellipsoidal terminal sets respect the
distributed structure, but may lead to conservative schemes. In this paper, a
novel distributed MPC scheme is proposed for reference tracking of networked
dynamical systems where the terminal ingredients are reconfigured online
depending on the closed-loop states to alleviate the aforementioned issues. The
resulting non-convex infinite-dimensional problem is approximated using a
quadratic program. The proposed scheme is tested in simulation where the
proposed MPC problem is solved using distributed optimization.
