Distributed Model-Predictive Control Driven by Simultaneous Derivation of Prices and Resources

A novel distributed model predictive control method for linear discrete-time systems is considered. The method can handle coupled constraints as well as coupled objective functions. For the decomposed optimal control problems embedded in the distributed controller additional linear information on the full optimal control problem is added. On each horizon, the resulting coordinated optimal control problem is solved iteratively. Prices and resources are calculated simultaneously. A convergence analysis is presented as well as a case study for an unstable process. There, an almost optimal control sequence is achieved after only one iteration.