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On convexity of stochastic optimization problems with constraints


M. Agarwal, E. Cinquemani, D. Chatterjee, J. Lygeros

European Control Conference (ECC), Budapest, Hungary, pp. 2827-2832

We investigate constrained optimal control problems for linear stochastic dynamical systems evolving in discrete time. We consider minimization of an expected value cost over a finite horizon. Hard constraints are introduced first, and then reformulated in terms of probabilistic constraints. It is shown that, for a suitable parametrization of the control policy, a wide class of the resulting optimization problems are either convex or amenable to convex relaxations.


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J. Lygeros

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