Robust design optimisation of dynamical space systems

Gianluca Filippi, M. Vasile, P. Z. Korondi, M. Marchi, C. Poloni

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In this paper we present a novel approach to the optimisation of complex systems affected by epistemic uncertainty when system and uncertainty evolve dynamically with time; we propose a new modelling approach that uses Evidence Theory to capture epistemic uncertainty A system is considered which is affected by the time during the operational life (failure rate, performance degradation, function degradation, etc.). The goal is to obtain a resilient design: robust with respect to performance variability and reliable against possible partial failures of one or more components. We propose to enhance the Evidence Network Model (ENM) with time-dependent reliability functions and decompose the problem into subproblems of smaller complexity. Through this decomposition uncertainty quantification of complex systems becomes affordable for a range of real-world applications. The method is here applied to a simple resource allocation problem where the goal is to optimally position subsystems within a spacecraft
Original languageEnglish
Number of pages1
Publication statusPublished - 28 Sep 2018
Event8th International Systems & Concurrent Engineering for Space Applications Conference - University of Strathclyde, Glasgow, United Kingdom
Duration: 26 Sep 201828 Sep 2018
Conference number: 8


Conference8th International Systems & Concurrent Engineering for Space Applications Conference
Abbreviated titleSECESA 2018
Country/TerritoryUnited Kingdom
Internet address


  • dynamical space systems
  • epistemic uncertainty
  • evidence network model
  • ENM
  • on-orbit space systems
  • space system design


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