Stochastic Model Predictive Control for Flight Path Angle Tracking of F-16 Aircraft based on Polynomial Chaos

Heri Purnawan*, Tahiyatul Asfihani, Seungkeun Kim, S. Subchan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Developing a reliable control system to manage Flight Path Angle (FPA) in the face of parameter uncertainties presents a challenge in F-16 Aircraft operations. This paper presents a novel approach, Stochastic Model Predictive Control (SMPC), utilized for FPA tracking amid probabilistic time-invariant parameters using Polynomial Chaos Expansion (PCE). A numerical case study employing longitudinal motion with uncertain parameters in aerodynamic coefficients within the system matrix validates the proposed method. Simulation results indicate that this approach exhibits greater robustness than nominal Model Predictive Control (MPC), with system outputs consistently aligning with the desired flight path angle value across all parameter realizations.

Original languageEnglish
Title of host publication2024 International Seminar on Intelligent Technology and Its Applications
Subtitle of host publicationCollaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages599-604
Number of pages6
Edition2024
ISBN (Electronic)9798350378573
DOIs
Publication statusPublished - 2024
Event25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024 - Hybrid, Mataram, Indonesia
Duration: 10 Jul 202412 Jul 2024

Conference

Conference25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024
Country/TerritoryIndonesia
CityHybrid, Mataram
Period10/07/2412/07/24

Keywords

  • F-16
  • flight path angle
  • parameter uncertainties
  • polynomial chaos
  • stochastic model predictive control

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