Fuzzy system reliability computation of the convoy of unmanned intelligent vehicles

Harpreet Singh; Arati M. Dixit; Adam Mustapha; Grant R. Gerhart

doi:10.1117/12.800419

16 October 2008 Fuzzy system reliability computation of the convoy of unmanned intelligent vehicles

Harpreet Singh, Arati M. Dixit, Adam Mustapha, Grant R. Gerhart

Proceedings Volume 7112, Unmanned/Unattended Sensors and Sensor Networks V; 71120Z (2008) https://doi.org/10.1117/12.800419
Event: SPIE Security + Defence, 2008, Cardiff, Wales, United Kingdom

Abstract

Unmanned intelligent ground vehicles play significant role in wide range of applications. They are of great significance in military applications as well as other commercial applications. In order to assure the performance of unmanned intelligent vehicles, it is important to predict the reliability of the system. Reliability can be calculated using different approaches as seen in the literature, but we propose a Graph theoretic approach supported by Fuzzy and Neuro-Fuzzy approaches for predicting the node and branch reliability of the system. We portray the convoy of unmanned vehicles as a communication network where the nodes represent the station of the convoy of unmanned intelligent vehicles and the branches would represent the path between two stations. The node and branch reliability is calculated using the Fuzzy and Neuro Fuzzy approaches. The terminal and system reliability would be calculated using Boolean algebra. Thus the overall system reliability of a convoy of vehicles is the result of Fuzzy, Neuro-Fuzzy and Boolean approaches. A spanning tree based algorithm is proposed for computation of the system reliability of a convoy of vehicles. We also propose to simulate the overall system reliability with some existing data of factors that contribute in computation of node and branch reliability.

Citation Download Citation

Harpreet Singh, Arati M. Dixit, Adam Mustapha, and Grant R. Gerhart "Fuzzy system reliability computation of the convoy of unmanned intelligent vehicles", Proc. SPIE 7112, Unmanned/Unattended Sensors and Sensor Networks V, 71120Z (16 October 2008); https://doi.org/10.1117/12.800419

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