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      Polynomial approximation of high-dimensional Hamilton-Jacobi-Bellman equations and applications to feedback control of semilinear parabolic PDEs

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          Abstract

          A procedure for the numerical approximation of high-dimensional Hamilton-Jacobi-Bellman (HJB) equations associated to optimal feedback control problems for semilinear parabolic equations is proposed. Its main ingredients are a pseudospectral collocation approximation of the PDE dynamics, and an iterative method for the nonlinear HJB equation associated to the feedback synthesis. The latter is known as the Successive Galerkin Approximation. It can also be interpreted as Newton iteration for the HJB equation. At every step, the associated linear Generalized HJB equation is approximated via a separable polynomial approximation ansatz. Stabilizing feedback controls are obtained from solutions to the HJB equations for systems of dimension up to fourteen.

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          A Markovian Decision Process

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            Galerkin approximations of the generalized Hamilton-Jacobi-Bellman equation

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              Some Convergence Results for Howard's Algorithm

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                Author and article information

                Journal
                2017-02-14
                Article
                1702.04400
                2dfa12ad-e627-497c-983c-0c333fe68056

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                math.OC math.NA

                Numerical & Computational mathematics,Numerical methods
                Numerical & Computational mathematics, Numerical methods

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