Advanced mechatronic systems often require decisions or control actions that go beyond classic control like setpoint tracking, e.g. coordination of multiple degrees of freedom or taking into account predictions of variable pricing or varying system parameters. Model-based methods (like MPC) can be used to solve these challenges, but are cumbersome and complex. Within this project we aim to use MPC, but as a benchmark, to assist the engineer in building or tuning simpler controllers that perform similarly to the optimum, but with reduced complexity.