Abstract
The paper deals with the problem of health-aware fault-tolerant control of a vehicle fleet. In particular, the development process starts with providing the description of the process along with a suitable Internet-of-Things platform, which enables appropriate communication within the vehicle fleet. It also indicates the transportation tasks to the designated drivers and makes it possible to measure their realization times. The second stage pertains to the description of the analytical model of the transportation system, which is obtained with the max-plus algebra. Since the vehicle fleet is composed of heavy duty machines, it is crucial to monitor and analyze the degradation of their selected mechanical components. In particular, the components considered are ball bearings, which are employed in almost every mechanical transportation system. Thus, a fuzzy logic Takagi–Sugeno approach capable of assessing their time-to-failure is proposed. This information is utilized in the last stage, which boils down to health-aware and fault-tolerant control of the vehicle fleet. In particular, it aims at balancing the exploitation of the vehicles in such a way as to maximize they average time-to-failure. Moreover, the fault-tolerance is attained by balancing the use of particular vehicles in such a way as to minimize the effect of possible transportation delays within the system. Finally, the effectiveness of the proposed approach is validated using selected simulation scenarios involving vehicle-based transportation tasks.