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 language | English |
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Title of host publication | 2024 International Seminar on Intelligent Technology and Its Applications |
Subtitle of host publication | Collaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 599-604 |
Number of pages | 6 |
Edition | 2024 |
ISBN (Electronic) | 9798350378573 |
DOIs | |
Publication status | Published - 2024 |
Event | 25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024 - Hybrid, Mataram, Indonesia Duration: 10 Jul 2024 → 12 Jul 2024 |
Conference
Conference | 25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024 |
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Country/Territory | Indonesia |
City | Hybrid, Mataram |
Period | 10/07/24 → 12/07/24 |
Keywords
- F-16
- flight path angle
- parameter uncertainties
- polynomial chaos
- stochastic model predictive control