On Implementation of Dynamic Programming for Optimal Control Problems with Final State Constraints
Résumé
In this paper we present issues related to the implementation of dynamic programming for
optimal control of a one-dimensional dynamic model, such as the hybrid electric vehicle
energy management problem. A study on the resolution of the discretized state space
emphasizes the need for careful implementation. A new method is presented to treat
numerical issues appropriately. In particular, the method deals with numerical problems
that arise due to high gradients in the optimal cost-to-go function. These gradients
mainly occur on the border of the feasible state region. The proposed method not only
enhances the accuracy of the final global optimum but also allows for a reduction of the
state-space resolution with maintained accuracy. The latter substantially reduces the
computational effort to calculate the global optimum. This allows for further applications
of dynamic programming for hybrid electric vehicles such as extensive parameter
studies.
Domaines
Physique [physics]
Origine : Publication financée par une institution