In this paper a new, adaptive cooperative form of robust distributed model predictive control is introduced. In the new algorithm, for linear, dynamically-decoupled subsystems in the presence of bounded disturbances, an optimizing subsystem determines the existence of paths in a graph representing currently-active coupling constraints. Where such paths exists, cooperation is promoted by the local agent designing a hypothetical plan for other subsystems. Robust feasibility and stability are maintained by permitting only non-coupled agents to update at each time step. By simulation, performance is shown to surpass that of using cooperation between immediately-adjacent agents, rivalling that of a "fully cooperative" implementation.
|Translated title of the contribution||Adaptive Cooperation in Robust Distributed Model Predictive Control|
|Title of host publication||IEEE Multi-conference on Systems and Control (MSC) incorporating the International Symposium on Intelligent Control (ISIC), St Petersburg|
|Publication status||Published - Jul 2009|