LAUSR

Abstract The current trend towards Industry 4.0 leads to several important aspects that concern future warehouse systems. The holistic digitalization efforts behind this trend may enable sustainable and resilient processes within warehouses and may increase their agility, but require elaborate control and diagnosis systems. This paper concentrates on one prominent means for increasing the agility - the employment of multiple automated guided vehicles (AGVs). Due to the complexity of a system with multiple AGVs, model predictive control (MPC) algorithms are required for effective and efficient operation. In industrial reality, uncertainties cannot be avoided, it is therefore highly desirable that these algorithms can handle such uncertainties and minor inconsistencies. The precedent necessities led to a strategy based on a fault-tolerant control framework, which is based on max-plus algebra with a model predictive control scheme. The applicability of this strategy is validated on the example of the feedings system of an high-bay warehouse.