The main idea behind optimal paperpath control using dynamic programming (DP) was presented earlier this year. This talk will briefly repeat some of the basics before discussing new results, which center around a reachability analysis. By calculating the backwards reachset, I will illustrate how one can answer the following questions:

- What is the minimal paperpath length required to handle all physically possible combinations of initial errors?

- DP offers a state feedback control law. The state of the system is determined by sheet positions, which are unknown until sheets are fed. How can we use the DP solution for N sheets without full state knowledge (i.e. number of sheets fed < N)?

- Is it possible to control a copyjob of arbitrary size M (i.e. M copies to be made) without solving a DP problem of size M? The current results are limited to simplified single integrator dynamics. The extension to a double integrator model is easy to do, but requires more computing time and memory. Conclusions will focus on how the DP approach can guide paperpath design rules.