Abstract
Networked control problems of multi-agent systems can be distributed to
the agents to reduce computational effort. One distribution strategy is
priority-based non-cooperative distributed model predictive control
(P-DMPC), in which the computation time is mainly determined by the
longest path in the coupling directed acyclic graph (DAG). The longest
path is dependent on the undirected coupling graph, which is fixed, and
the priority assignment, which is variable. This article presents an
approach to assign priorities in P-DMPC to reduce the longest path
length in the coupling DAG and therefore the computation time for the
networked control system (NCS). We proof that this problem can be mapped
to a graph-coloring problem, in which the number of needed colors
corresponds to the longest path length in the coupling DAG. We present
an efficient graph-coloring algorithm from which we determine priorities
for the agents. We evaluate effect and effort of the approach before
applying it to trajectory planning for networked vehicles at
intersections.