Analysis of an UAV flight control system using probabilistic μ

Gary J. Balas, Peter J. Seiler, Andrew K. Packard

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

5 Scopus citations

Abstract

Robustness analysis in the structured singular value (μ) framework is a worst-case paradigm which may be conservative in cases where the exact coalescence of worst model in the set is unlikely to occur. Rather one may be interested in assessing the risk of unlikely events to occur. Traditionally this leads to a probabilistic approach to assessing risk and these questions have been approached using Monte Carlo methods of sampling the parameter space to approximate the probability distribution of the parameters. Probabilistic μ or probabilistic gain was formulated to provide a bridge between worst-case analysis techniques and probabilistic measures of rare events. This paper describes the application probabilistic gain metrics to the NASA Generic Transport Model (GTM) aircraft. Probabilistic μ analysis results are compared with worst-case and Monte Carlo analysis to highlight the potential benefits of combining worst-case analysis with traditional probabilistic methods.

Original languageEnglish (US)
Title of host publicationAIAA Guidance, Navigation, and Control Conference 2012
StatePublished - Dec 1 2012
EventAIAA Guidance, Navigation, and Control Conference 2012 - Minneapolis, MN, United States
Duration: Aug 13 2012Aug 16 2012

Publication series

NameAIAA Guidance, Navigation, and Control Conference 2012

Other

OtherAIAA Guidance, Navigation, and Control Conference 2012
CountryUnited States
CityMinneapolis, MN
Period8/13/128/16/12

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  • Cite this

    Balas, G. J., Seiler, P. J., & Packard, A. K. (2012). Analysis of an UAV flight control system using probabilistic μ. In AIAA Guidance, Navigation, and Control Conference 2012 (AIAA Guidance, Navigation, and Control Conference 2012).