The use of discrete adjoints in the context of a hard time-dependent optimal control problem is considered. Gradients required for the steepest descent method are computed by code that is generated automatically by the differentiation-enabled NAGWare Fortran compiler. Single time steps are taped using an overloading approach. The entire evolution is reversed based on an efficient checkpointing schedule that is computed by revolve. The feasibility of nonlinear optimization based on discrete adjoints is supported by our numerical results.