Integrated Guidance and Control of Quasi-Equilibrium Hypersonic Gliding Using Model Predictive Control

This paper presents a guidance and control framework for hypersonic glide vehicles (HGVs) in atmospheric re-entry missions, wherein the guidance is designed in conjunction with the flight controls to synergistically integrate mission requirements with capabilities of the airframe, resulting in a comprehensive design and analysis architecture. Three-dimensional motion of the vehicle—executing a constant dynamic pressure glide subject to quasi-equilibrium conditions—is considered under the assumption that bank angle can be modulated directly. The proposed guidance subsystem computes trajectories that enable gliding at a specified dynamic pressure despite perturbations caused by initialization errors and/or external disturbances during flight. Inclusion of bank angle extends the feasible trajectory design space, thereby promoting flexibility of operation and providing the option to include additional mission-related requirements. The trajectory computation is online and inherently coupled with the flight controller which synthesizes the control inputs—stabilator deflection and bank angle—for trajectory tracking using a linear time-varying model predictive control design that embeds box constraints on the control input magnitudes. Closed-loop simulations of a generic HGV are used to demonstrate robust tracking of trajectories subject to plant-model mismatch and initialization errors. Load factors and heat fluxes are analyzed along simulated closed-loop trajectories, with the former converging to a constant value after transient oscillations initially and the latter showcasing an approximately monotonic decrease throughout.

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Publication Details

Published
2025-07-16
DOI
https://doi.org/10.2514/6.2025-3550
Citations
1
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
1.21
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article

Integrated Guidance and Control of Quasi-Equilibrium Hypersonic Gliding Using Model Predictive Control

Maziar S. Hemati, Diganta Bhattacharjee, Sam Jaeger
1 citations
Adaptive Control of Nonlinear Systems
1.21
article

Integrated Guidance and Control of Quasi-Equilibrium Hypersonic Gliding Using Model Predictive Control

Maziar S. Hemati, Diganta Bhattacharjee, Sam Jaeger
article en
1 citations

Abstract

This paper presents a guidance and control framework for hypersonic glide vehicles (HGVs) in atmospheric re-entry missions, wherein the guidance is designed in conjunction with the flight controls to synergistically integrate mission requirements with capabilities of the airframe, resulting in a comprehensive design and analysis architecture. Three-dimensional motion of the vehicle—executing a constant dynamic pressure glide subject to quasi-equilibrium conditions—is considered under the assumption that bank angle can be modulated directly. The proposed guidance subsystem computes trajectories that enable gliding at a specified dynamic pressure despite perturbations caused by initialization errors and/or external disturbances during flight. Inclusion of bank angle extends the feasible trajectory design space, thereby promoting flexibility of operation and providing the option to include additional mission-related requirements. The trajectory computation is online and inherently coupled with the flight controller which synthesizes the control inputs—stabilator deflection and bank angle—for trajectory tracking using a linear time-varying model predictive control design that embeds box constraints on the control input magnitudes. Closed-loop simulations of a generic HGV are used to demonstrate robust tracking of trajectories subject to plant-model mismatch and initialization errors. Load factors and heat fluxes are analyzed along simulated closed-loop trajectories, with the former converging to a constant value after transient oscillations initially and the latter showcasing an approximately monotonic decrease throughout.

University of Minnesota (US), Twin Cities Orthopedics (US)
Climate action
Openalex Percentile: Top 19%
Adaptive Control of Nonlinear Systems
1.21
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