Dragos N. Clipici

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In this paper we employ a parallel version of a randomized (block) coordinate descent method for minimizing the sum of a partially separable smooth convex function and a fully separable nonsmooth convex function. Under the assumption of Lipschitz continuity of the gradient of the smooth function, this method has a sublinear convergence rate. Linear(More)
— This paper focuses on distributed model predictive control for large-scale systems comprised of interacting linear subsystems, where the necessary online computations can be distributed amongst them. A model predictive controller based on a distributed interior point method is derived, in which stabilizing control inputs can be computed distributively by(More)
In this paper we propose a linear MPC scheme for embedded systems based on the dual fast gradient algorithm for solving the corresponding control problem. We establish computational complexity guarantees for the MPC scheme by appropriately deriving tight convergence estimates of order O(1/k<sup>2</sup>) for an average primal sequence generated by our(More)
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