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Convergence rates of moment-sum-of-squares hierarchies for optimal control problems

Milan Korda (korda.m***at***gmail.com)
Didier Henrion (henrion***at***laas.fr)
Colin N. Jones (colin.jones***at***epfl.ch)

Abstract: We study the convergence rate of moment-sum-of-squares hierarchies of semidefinite programs for optimal control problems with polynomial data. It is known that these hierarchies generate polynomial under-approximations to the value function of the optimal control problem and that these under-approximations converge in the $L^1$ norm to the value function as their degree $d$ tends to infinity. We show that the rate of this convergence is $O(1/\log\log\,d)$. We treat in detail the continuous-time infinite-horizon discounted problem and describe in brief how the same rate can be obtained for the finite-horizon continuous-time problem and for the discrete-time counterparts of both problems.

Keywords: optimal control, moment relaxations, polynomial sums of squares, semidefinite programming, approximation theory

Category 1: Linear, Cone and Semidefinite Programming (Semi-definite Programming )

Category 2: Applications -- Science and Engineering (Control Applications )

Category 3: Nonlinear Optimization (Systems governed by Differential Equations Optimization )

Citation:

Download: [PDF]

Entry Submitted: 09/08/2016
Entry Accepted: 09/08/2016
Entry Last Modified: 09/08/2016

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