Resumen
While the growth of unmanned aerial vehicle (UAV) usage over the next few years is indisputable, cooperative operation strategies for UAV swarms have gained great interest in the research community. Mission capabilities increase while contingencies can be mitigated through intelligent management between the operating swarm and the available fleet. The importance of observing the system reliability and of risk assessment grows because the dysfunction of one asset within a system of systems endangers the superordinate mission goals of the operating UAV swarm. Thus, not only is trajectory planning beneficial for usage optimization, but prognostic and health management (PHM) methods, including diagnostics and prognostics, also enable situational awareness and condition-driven asset management to achieve higher mission reliability. The novelty of this work is the observation of asset states based upon a generically modeled multi-component degradation behavior and the integration of PHM methods with real-time capabilities in order to support decision making during mission execution in a highly dynamic and event-based environment. The developed simulation enables the testing and comparison of different maintenance strategies that are integrated into the simulation to show and discuss the effectiveness and benefits of real-time-capable PHM methods.