An Error Estimate for Symplectic Euler Approximation of Optimal Control Problems

Peer Jesper Karlsson, Stig Larsson, Mattias Sandberg, Anders Szepessy, Raul Tempone

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This work focuses on numerical solutions of optimal control problems. A time discretization error representation is derived for the approximation of the associated value function. It concerns symplectic Euler solutions of the Hamiltonian system connected with the optimal control problem. The error representation has a leading-order term consisting of an error density that is computable from symplectic Euler solutions. Under an assumption of the pathwise convergence of the approximate dual function as the maximum time step goes to zero, we prove that the remainder is of higher order than the leading-error density part in the error representation. With the error representation, it is possible to perform adaptive time stepping. We apply an adaptive algorithm originally developed for ordinary differential equations. The performance is illustrated by numerical tests.
Original languageEnglish (US)
Pages (from-to)A946-A969
Number of pages1
JournalSIAM Journal on Scientific Computing
Issue number2
StatePublished - Jan 2015

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01


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