Engineering processes often require optimizing model variables for satisfactory solutions. Reliable approaches exist in literature but are application-dependent. In that sense, metaheuristics have been proven to deliver outstanding results while imposing a low computing burden. However, choosing the most suitable one from the many available can overwhelm even experts. This study implements a methodology that automatically tailors a problem-based metaheuristic through a hyper-heuristic approach. We select the tuning problem of a Proportional Integral Derivative controller as a case study for achieving the best stable features in an Automatic Voltage Regulator system. The numerical results demonstrate the reliability and potential of the implemented methodology in solving control system tuning. Plus, we conduct an in-depth quantitative comparison with recent works in the literature that support those conclusions.