Local minimization algorithms for dynamic programming equations
The numerical realization of the dynamic programming principle for continuous-time optimal
control leads to nonlinear Hamilton--Jacobi--Bellman equations which require the
minimization of a nonlinear mapping over the set of admissible controls. This minimization is
often performed by comparison over a finite number of elements of the control set. In this
paper we demonstrate the importance of an accurate realization of these minimization
problems and propose algorithms by which this can be achieved effectively. The considered …
control leads to nonlinear Hamilton--Jacobi--Bellman equations which require the
minimization of a nonlinear mapping over the set of admissible controls. This minimization is
often performed by comparison over a finite number of elements of the control set. In this
paper we demonstrate the importance of an accurate realization of these minimization
problems and propose algorithms by which this can be achieved effectively. The considered …
The numerical realization of the dynamic programming principle for continuous-time optimal control leads to nonlinear Hamilton--Jacobi--Bellman equations which require the minimization of a nonlinear mapping over the set of admissible controls. This minimization is often performed by comparison over a finite number of elements of the control set. In this paper we demonstrate the importance of an accurate realization of these minimization problems and propose algorithms by which this can be achieved effectively. The considered class of equations includes nonsmooth control problems with -penalization which lead to sparse controls.
Society for Industrial and Applied Mathematics