Asynchronous cooperative method for distributed model predictive control

In this paper we consider a distributed solution of the model predictive control problem (DMPC), based on the block version of the Jacobi algorithm applied to the dual problem. In order to accelerate the convergence, a Nesterov's schema can be considered, but the updating rule coming out in such way is fully distributed and parallel, but synchronous. This assumption is often unrealistic in real-life large-scale systems. For this reason an asynchronous version of the method has been proposed and the convergence properties have been studied. Numerical experiments show the effectiveness of the approach by comparing it with the methods presented in the literature.

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