L1 Adaptive Augmentation of an Incremental Nonlinear Dynamic Inversion Autopilot for Dual-Spin Guided Projectiles

Conference Paper (2023)
Author(s)

Sofiane Pineau (Lorraine University)

S.T. Theodoulis (TU Delft - Aerospace Engineering)

Michel Zasadzinski (Lorraine University)

Mohamed Boutayeb (Lorraine University)

Emmanuel Roussel (French-German Research Institute of Saint-Louis)

Research Group
Control & Simulation
DOI related publication
https://doi.org/10.2514/6.2023-1998 Final published version
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Publication Year
2023
Language
English
Research Group
Control & Simulation
Article number
AIAA 2023-1998
ISBN (electronic)
978-1-62410-699-6
Event
AIAA SCITECH 2023 Forum (2023-01-23 - 2023-01-27), National Harbor, MD & Online, Washington, United States
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Abstract

This article covers the design of an L1-adaptive Incremental Nonlinear Dynamic Inversion (INDI) autopilot applied to the control of the ballistic trajectory of a 155mm dual-spin projectile supplied with a roll-decoupled course-correction fuze. Associated with a Zero Effort Miss guidance law, the discrete-time INDI baseline successfully controls the lateral load factors of the projectile, resulting in a ballistic dispersion reduced to metric precision. However, aerodynamic data for dual-spin projectiles are often not very accurate because they rely on simplified CFD simulation and time-consuming wind tunnel tests aren’t always possible. Therefore significant parametric uncertainties are present in the model. Even if INDI is a sensor-based control technique, this approach is still sensitive to model mismatch. For this reason, L1-adaptive control theory was used to compensate for the degraded inversion of the INDI autopilot under the presence of parametric uncertainties. Nonlinear simulation results show the interest of an L1-adaptive augmentation of an INDI autopilot where the performance of the autopilot is guaranteed under a large range of time-varying matched uncertainties

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