A new self-adaptive mission aborting policy for systems operating in uncertain random shock environment

For systems operating in random shock environment, mission aborting policies based on the number of shocks experienced during a certain time interval are common and have received intensive attention. However, the number of shocks-based aborting policy (NSAP) is not effective when the shock rate during the primary mission is uncertain because it cannot adapt itself to the shock rate. This paper puts forward a new, self-adaptive inter-shock interval-based aborting policy (ISIAP), which determines the inter-shock interval within which the primary mission should be aborted upon the next shock based on the previous inter-shock interval. A probabilistic approach is suggested for assessing the mission success probability (MSP) and the system survival probability (SSP) under a given ISIAP. The optimal ISIAP problem is formulated and solved with the objective to maximize the expected MSP while meeting certain requirement on the SSP. A detailed case study of an unmanned aerial vehicle performing a payload delivery mission is provided to demonstrate the proposed mission aborting model and compare the effectiveness of the proposed ISIAP and the conventional NSAP. Impacts of the SSP requirement and the shock rate parameter on the mission performance metrics and optimal solutions are also examined in the case study.