DistributedRecedingHorizonControlwithApplication to Multi-VehicleFormationStabilization?

We consider the control of interacting subsystems whose dynamics and constraints are decoupled, but whose state vectors are coupled non-separably in a single cost function of a finite horizon optimal control problem. For a given cost structure, we generate distributed optimal control problems for each subsystem and establish that a distributed receding horizon control implementation is stabilizing to a neighborhood of the objective state. The implementation requires synchronous updates and the exchange of the most recent optimal control trajectory between coupled subsystems prior to each update. The key requirements for stability are that each subsystem not deviate too far from the previous open-loop state trajectory, and that the receding horizon updates happen sufficiently fast. The venue of multi-vehicle formation stabilization is used to demonstrate the distributed implementation and simulation experiments are provided. The extension to handle coupling state constraints is also discussed. Key words: receding horizon control; model predictive control; distributed control; decentralized control; large scale systems; multi-vehicle formations; coordinated robots.