Polynomial chaos-based flight control optimization with guaranteed probabilistic performance

Dalong Shi, Xiang Fang, Florian Holzapfel

Research output: Contribution to journalConference articlepeer-review

6 Scopus citations

Abstract

A probabilistic performance-oriented controller design approach based on polynomial chaos expansion and optimization is proposed for flight dynamic systems. Unlike robust control techniques where uncertainties are conservatively handled, the proposed method aims at propagating uncertainties effectively and optimizing control parameters to satisfy the probabilistic requirements directly. To achieve this, the sensitivities of violation probabilities are evaluated by the expansion coefficients and the fourth moment method for reliability analysis, after which an optimization that minimizes failure probability under chance constraints is conducted. Afterward, a time-dependent polynomial chaos expansion is performed to validate the results. With this approach, the failure probability is reduced while guaranteeing the closed-loop performance, thus increasing the safety margin. Simulations are carried out on a longitudinal model subject to uncertain parameters to demonstrate the effectiveness of this approach.

Original languageEnglish
Pages (from-to)7274-7279
Number of pages6
JournalIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume53
Issue number2
DOIs
StatePublished - 2020
Event21st IFAC World Congress 2020 - Berlin, Germany
Duration: 12 Jul 202017 Jul 2020

Keywords

  • Flight control optimization
  • Polynomial chaos expansion
  • Probabilistic performance

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