Model-predictive spiral and spin upset recovery control for the generic transport model simulation

Torbjorn Cunis, Dominic Liao-Mcpherson, Ilya Kolmanovsky, Laurent Burlion

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

Abstract

Aircraft upsets are a major cause of fatalities in civil aviation. Unfortunately, recovery from upset scenarios is challenging due to the combination of nonlinearities, actuator limits, and upset modes. In this paper, we consider the use of Model-Predictive Control (MPC) in combination with a recently proposed piecewise polynomial prediction model, for six degree-of-freedom upset recovery. MPC naturally handles nonlinearities and constraints and has a provably large closed-loop region of attraction making it an appealing methodology for upset recovery problems. We present a recovery formulation then illustrate its utility through high fidelity simulation case studies, using the Generic Transport Model, of recovery from oscillatory spin and steep spiral upset conditions.

Original languageEnglish (US)
Title of host publicationCCTA 2020 - 4th IEEE Conference on Control Technology and Applications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-7
Number of pages7
ISBN (Electronic)9781728171401
DOIs
StatePublished - Aug 2020
Event4th IEEE Conference on Control Technology and Applications, CCTA 2020 - Virtual, Montreal, Canada
Duration: Aug 24 2020Aug 26 2020

Publication series

NameCCTA 2020 - 4th IEEE Conference on Control Technology and Applications

Conference

Conference4th IEEE Conference on Control Technology and Applications, CCTA 2020
Country/TerritoryCanada
CityVirtual, Montreal
Period8/24/208/26/20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Control and Optimization
  • Instrumentation

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