Abstract
AbstractBecause of the environments in which they will operate, future autonomous systems must be capable of reconfiguring quickly and safely following faults or environmental changes. Past research has shown how, by considering autonomous systems to perform phased missions, reliability analysis can support decision making by allowing comparison of the probability of success of different missions following reconfiguration. Binary decision diagrams (BDDs) offer fast, accurate reliability analysis that could contribute to real‐time decision making. However, phased mission analysis using existing BDD models is too slow to contribute to the instant decisions needed in time‐critical situations. This paper investigates 2 aspects of BDD models that affect analysis speed: variable ordering and quantification efficiency. Variable ordering affects BDD size, which directly affects analysis speed. Here, a new ordering scheme is proposed for use in the context of a decision‐making process. Variables are ordered before a mission, and reordering is unnecessary no matter how the mission configuration changes. Three BDD models are proposed to address the efficiency and accuracy of existing models. The advantages of the developed ordering scheme and BDD models are demonstrated in the context of their application within a reliability analysis methodology used to support decision making in an unmanned aerial vehicle.
Highlights
Systems that perform a sequence of tasks in order to achieve a specific objective are called phased mission systems (PMS)
The work presented in this paper aims to address the requirement for fast, accurate calculation of updated unreliability, by proposing two amendments to the Binary Decision Diagrams (BDDs) model presented in[7] in order to correct inaccuracies that have been highlighted in past research[8 12], and proposing a more efficient quantification method for the BDD model presented in[8]
If a reliability analysis methodology is to be used to support real-time decision making for systems operating phased missions in changing mission environments, it is crucial that the applied methodology can analyze PMS quickly and accurately
Summary
Systems that perform a sequence of tasks in order to achieve a specific objective are called phased mission systems (PMS). A mission configuration is defined according to the tasks that must be completed, the time duration of each task and the sequence of the tasks. PMS such as those carried out by a UAV are non-repairable since repairs are not possible during a mission. A BDD node is represented by an if--else (ite) structure:. The BDD is traversed in this way until a terminal node, with a value of 0 or 1, is reached. The variable ordering can significantly impact the BDD size[10], which is measured by the number of distinct non-terminal nodes the BDD contains, and the time taken to perform analysis
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