Resilience Optimization for Complex Engineered Systems Based on the Multi-Dimensional Resilience Concept

Research output: Contribution to journalArticlepeer-review

Abstract

Most traditional engineered syrtems are designed with a passive and fixed reliability capability and just required to achieve a possibly low level of failure occurrence. However, as the complexity at spatial-temporal scales and integrations increases, modern complex engineered systems (CESs) are facing new challenges of inherent risk and bottleneck for a successful and safe operation through the system life cycle when potential expected or unexpected disruptive events happen. As a prototype for ensuring the successful operation of inherently risky systems, resilience has demonstrated itself to be a promising concept to address the above-mentioned challenges. A standard multi-dimensional resilience triangle model is first presented based on the concept of the three-phase system resilience cycle, which can provide a theoretical foundation for indicating the utility objectives of resilience design. Then, the resilience design problem for CESs is proposed as a multi-objective optimization model, in which the three objectives are to maximize the survival probability, to maximize the reactive timeliness and to minimize the total budgeted cost. Furthermore, the proposed multi-objective optimization programming is solved based on the efficient multi-objective evolutionary algorithm NSGA-II. Finally, the effectiveness of the proposed models and solving procedure is illustrated with an engineered electro-hydrostatic aircraft control actuator resilience design problem, a comparative analysis on the case study is also carried out with respect to previous works. This work can provide an effective tradeoff foundation to improve the resilience of CESs.

Original languageEnglish
Article number8047936
Pages (from-to)19352-19362
Number of pages11
JournalIEEE Access
Volume5
DOIs
StatePublished - 20 Sep 2017

Keywords

  • NSGA-II
  • Resilience
  • complex engineered systems
  • multi-dimensional model
  • multi-objective programming

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