Development of a key performance indicator framework for automated warehouse systems

Designing effective braking controllers for aircrafts is a challenging task, due to the highly time-varying dynamical features and the very different working conditions of interest. Traditional controllers rely on threshold-based acceleration approaches, but it has been recently proved that slip-based solutions can enhance performance and allow direct tire monitoring. However, also slip-based solutions need adaptation. This paper shows how this can be achieved via LPV data-driven design, with an approach that has its major strength in easing the controller design phase, as it learns both controller parameters and scheduling functions from data. The proposed slip controller ensures both safety and performance, and it is tested within a very realistic simulation setting, endowed with measured noises due to slip estimation errors.