Multidisciplinary design optimisation of Unmanned Aerial Systems (UAS) using Meta model Assisted Evolutionary Algorithms

L. F. Gonzalez*, R. Walker, K. Srinivas, J. Periaux

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Abstract

Unmanned Aerial Systems (UAS) is recognised to be the next revolution in aviation as information technology matures in the aerospace sector. UAS systems are multidiscipline systems as they integrate several disciplines, e.g. avionics, flight control, aerodynamics, structures. The design and optimisation of these vehicles can be multi-modal, non-convex or discontinuous, with multiple local minima and with noise. Traditional gradient based optimisation method might fail to find true optimal solutions or Pareto Fronts. This paper explores the design and coupling of Meta-model Assisted (MMA) with Multi-Objective Evolutionary Algorithms (MOEA) for Unmanned Aerial Systems (UAS) design. Results indicate an improvement on optimisation performance and both practicality and robustness of the method in finding optimal solutions and Pareto trade-offs between the disciplines.

Original languageEnglish
Title of host publicationProceedings of the 16th Australasian Fluid Mechanics Conference, 16AFMC
EditorsPeter Jacobs, Tim McIntyre, Matthew Cleary, David Buttsworth, David Mee, Rose Clements, Richard Morgan, Charles Lemckert
Place of PublicationSt. Lucia, Qld
PublisherSchool of Engineering, University of Queensland
Pages471-474
Number of pages4
ISBN (Print)9781864998948
Publication statusPublished - 2007
Event16th Australasian Fluid Mechanics Conference, 16AFMC - Gold Coast, QLD, Australia
Duration: 3 Dec 20077 Dec 2007

Other

Other16th Australasian Fluid Mechanics Conference, 16AFMC
CountryAustralia
CityGold Coast, QLD
Period3/12/077/12/07

Fingerprint Dive into the research topics of 'Multidisciplinary design optimisation of Unmanned Aerial Systems (UAS) using Meta model Assisted Evolutionary Algorithms'. Together they form a unique fingerprint.

  • Cite this

    Gonzalez, L. F., Walker, R., Srinivas, K., & Periaux, J. (2007). Multidisciplinary design optimisation of Unmanned Aerial Systems (UAS) using Meta model Assisted Evolutionary Algorithms. In P. Jacobs, T. McIntyre, M. Cleary, D. Buttsworth, D. Mee, R. Clements, R. Morgan, ... C. Lemckert (Eds.), Proceedings of the 16th Australasian Fluid Mechanics Conference, 16AFMC (pp. 471-474). St. Lucia, Qld: School of Engineering, University of Queensland.