Aerospace

Research

19 pages, 333 KB

Open AccessArticle

Sparse Single-Use Thruster Selection for Control Moment Tracking Using a Depth-First Branch-and-Bound Algorithm

by Ha-min Jeon and Tae Young Kang

Aerospace 2026, 13(5), 450; https://doi.org/10.3390/aerospace13050450 - 10 May 2026

Viewed by 214

In high-altitude interception, low atmospheric density limits the effectiveness of aerodynamic control, making thruster-based attitude control essential. In systems using single-use impulse-type lateral thrusters, each actuator can be fired only once, generates a fixed thrust magnitude, and is subject to a limit on [...] Read more.

In high-altitude interception, low atmospheric density limits the effectiveness of aerodynamic control, making thruster-based attitude control essential. In systems using single-use impulse-type lateral thrusters, each actuator can be fired only once, generates a fixed thrust magnitude, and is subject to a limit on the number of simultaneously active thrusters. Therefore, selecting an appropriate set of thrusters to track a desired control moment can be formulated as a cardinality-constrained combinatorial optimization problem. This paper proposes a depth-first search (DFS)-based branch-and-bound algorithm for sparse thruster selection. The objective is to minimize the tracking error between the generated and desired control moments while penalizing the number of active thrusters. To improve computational efficiency, thrusters are ordered by moment magnitude, and a problem-specific lower bound is derived from the residual moment and an upper bound on the achievable contribution of the remaining thrusters. This bound enables effective pruning of unpromising branches. The search space is further reduced by reformulating the problem using symmetric thruster pairs that generate opposing moments. Numerical results show that the proposed method achieves accurate moment tracking while significantly reducing computation time compared with the exact mixed-integer quadratic programming (MIQP) benchmark. Mixed-integer linear programming (MILP) is also included as an additional mixed-integer linear surrogate comparison. Full article

(This article belongs to the Special Issue Flight Guidance and Control)

► Show Figures

Figure 1

17 pages, 1612 KB

Open AccessArticle

A Flight Path Angle Reconstruction-Based Polynomial Guidance Law with Multiple Constraints

by Hong Liang, Zechen Zhang and Sijiang Chang

Aerospace 2026, 13(4), 386; https://doi.org/10.3390/aerospace13040386 - 20 Apr 2026

Viewed by 348

Abstract

A novel polynomial guidance law is proposed for flight vehicle terminal guidance, subject to multiple constraints including launch angle, impact angle, impact time, and zero terminal acceleration. This approach reconstructs the flight path angle profile into two components. One component satisfies the constraints. [...] Read more.

A novel polynomial guidance law is proposed for flight vehicle terminal guidance, subject to multiple constraints including launch angle, impact angle, impact time, and zero terminal acceleration. This approach reconstructs the flight path angle profile into two components. One component satisfies the constraints. The other ensures target interception. The constraint-oriented component is formulated as a polynomial function of the relative range-to-go. Based on this reconstruction framework, a new linearization approach is introduced to handle the nonlinear engagement kinematics. A closed-form guidance law is then derived to satisfy multiple constraints, and its convergence is analyzed theoretically. To optimize the control effort, a data-driven method is subsequently incorporated into the framework. Numerical simulation results show that the proposed guidance law achieves multiple constraints with high precision. Compared with existing methods, it also requires less control effort. Specifically, the impact angle error is within 0.02°, and the impact time error is within 0.05 s. Full article

(This article belongs to the Special Issue Flight Guidance and Control)

► Show Figures

Figure 1

32 pages, 12012 KB

Open AccessArticle

Multi-Agent Reinforcement Learning-Based Intelligent Game Guidance with Complex Constraint

by Fucong Liu, Yang Guo, Shaobo Wang, Jin Wang and Zhengquan Liu

Aerospace 2026, 13(4), 365; https://doi.org/10.3390/aerospace13040365 - 14 Apr 2026

Viewed by 463

Abstract

For the complex problems of multi-aircraft cooperative game guidance with No-Fly Zone (NFZ) avoidance and cross-task constraint propagation, a deep deterministic policy gradient algorithm with temporal awareness and priority cooperative optimization (TP-MADDPG) is proposed. Based on the three-body cooperative guidance, a new coupled [...] Read more.

For the complex problems of multi-aircraft cooperative game guidance with No-Fly Zone (NFZ) avoidance and cross-task constraint propagation, a deep deterministic policy gradient algorithm with temporal awareness and priority cooperative optimization (TP-MADDPG) is proposed. Based on the three-body cooperative guidance, a new coupled guidance task is formed by adding the NFZ avoidance constraint. At the same time, considering the constraint compatibility problem in dynamic task switching, the cooperative aircraft are modeled as independent agents with differentiated policy networks. First, a nonlinear kinematic model of the three-body game constructed by Evader–Pursuer–Defender is established. And four complex constraint conditions, namely homing guidance, NFZ avoidance, collision avoidance, and cooperative guidance, are modeled separately. Secondly, the Long Short-Term Memory-based (LSTM) Actor–Critic framework is proposed to dynamically capture the evolution patterns of adversarial scenarios by mining hidden correlations in historical state-action sequences. This enables smooth policy transitions between the cooperative guidance phase and subsequent homing guidance phase, effectively addressing the challenges of environmental non-stationarity and temporal task dependencies. Then, a priority-driven adaptive sampling mechanism is proposed along with a heterogeneous roles cooperative reward function to specifically address credit assignment imbalance and sparse reward problems, respectively. The sampling mechanism capitalizes on the efficient retrieval properties of SumTree data structures while integrating bias correction techniques to expedite policy gradient convergence. The reward function utilizes the reward shaping method to formulate cooperative reward components that explicitly capture behavioral correlations among agents. Finally, simulations show that the proposed method significantly outperforms multi-agent reinforcement learning baselines, effectively improving the performance of cooperative game guidance under complex constraints. Full article

(This article belongs to the Special Issue Flight Guidance and Control)

► Show Figures

Figure 1

16 pages, 411 KB

Open AccessArticle

Task Assignment for Loitering Munitions Based on Predicted Capturability

by Gyuyeon Choi, Seongwook Heu and Hyeong-Geun Kim

Aerospace 2026, 13(4), 347; https://doi.org/10.3390/aerospace13040347 - 8 Apr 2026

Viewed by 344

Abstract

This paper proposes a novel task assignment strategy for multiple fixed-wing loitering munitions, focusing on the kinematic capturability of maneuvering ground targets. Compared to rotary-wing UAVs, fixed-wing munitions are subject to significant turning radius constraints and limited maneuverability. Consequently, conventional assignment metrics based [...] Read more.

This paper proposes a novel task assignment strategy for multiple fixed-wing loitering munitions, focusing on the kinematic capturability of maneuvering ground targets. Compared to rotary-wing UAVs, fixed-wing munitions are subject to significant turning radius constraints and limited maneuverability. Consequently, conventional assignment metrics based on relative distance or estimated time-to-go are insufficient to guarantee successful interception. To address this, we adopt a data-driven capturability prediction framework based on Gaussian Process Regression (GPR) and propose a novel task assignment strategy that leverages the predicted capture region as a decision-making criterion. Furthermore, a robustness-centric task assignment algorithm is proposed, which prioritizes interceptors based on the radius of the Maximum Inscribed Circle (MIC) within the predicted capture region. This metric quantifies the safety margin against target maneuvers and environmental uncertainties. Numerical simulations demonstrate that the proposed method significantly outperforms conventional distance-based and time-to-go-based approaches, achieving the highest interception success rate across all tested scenarios including maneuvering target conditions. The results validate that incorporating geometric capturability constraints is essential for the efficient operation of fixed-wing loitering munitions. Full article

(This article belongs to the Special Issue Flight Guidance and Control)

► Show Figures

Figure 1

23 pages, 1036 KB

Open AccessArticle

Reusability Flight Experiment Guidance: Trajectory Correction After Ascent

by Jose Luis Redondo Gutierrez, David Seelbinder and Stephan Theil

Aerospace 2025, 12(9), 838; https://doi.org/10.3390/aerospace12090838 - 17 Sep 2025

Viewed by 1141

Abstract

This paper presents the design and implementation of a guidance algorithm for the re-entry vehicle ReFEx (Reusability Flight Experiment). This algorithm aims at correcting for the dispersion in position and velocity after separation from the launcher, by updating the trajectory. The need for [...] Read more.

This paper presents the design and implementation of a guidance algorithm for the re-entry vehicle ReFEx (Reusability Flight Experiment). This algorithm aims at correcting for the dispersion in position and velocity after separation from the launcher, by updating the trajectory. The need for this update is driven by the expected divergence from the nominal trajectory at separation, due to the use of an unguided launcher. The transcription of the problem into an optimal control problem is used as a baseline for verification purposes. This algorithm consists of a simplification of the optimal control problem, reducing the profiles of the control variables to a finite set of control parameters. Combining this problem reduction with a function that propagates the trajectory from the initial state, this approach is able to transform the problem into an unconstrained optimization problem. This paper shows that this simplification is able to find solutions of similar quality to the full optimal control approach. The resulting algorithm is proven real-time capable by deploying it into a hardware equivalent of the on-board computer. In addition, a strategy to diverge during flight to an alternative target if the nominal one cannot be reached is appended to the algorithm. Full article

(This article belongs to the Special Issue Flight Guidance and Control)

► Show Figures

Figure 1

17 pages, 4787 KB

Open AccessArticle

The Development of a Prototype for Low Altitude Operations of Unmanned Aircraft Flight Plan Systems

by Siriporn Yenpiem, Soemsak Yooyen, Anucha Tungkasthan, Sasicha Banchongaksorn and Keito R. Yoneyama

Aerospace 2025, 12(9), 826; https://doi.org/10.3390/aerospace12090826 - 15 Sep 2025

Viewed by 1283

Abstract

The use of Unmanned Aircraft has grown significantly in Thailand and worldwide, particularly for operations below 450 feet. However, unlike manned aviation, there remains a lack of integrated digital platforms to manage flight plans that align with regulatory and operational requirements specific to [...] Read more.

The use of Unmanned Aircraft has grown significantly in Thailand and worldwide, particularly for operations below 450 feet. However, unlike manned aviation, there remains a lack of integrated digital platforms to manage flight plans that align with regulatory and operational requirements specific to low altitude activity. This study employed both secondary research and expert interviews to gather technical and regulatory user requirements. The data were analyzed and validated using Structural Equation Modeling to identify key variables influencing safety operations. Based on these findings, a standardized low altitude flight plan format was developed and converted into a prototype web platform called GoFly. The system enables operators to register aircraft and pilot credentials and to submit flight plans digitally. This platform addresses the current fragmentation in Thailand’s flight planning process by centralizing operations and enhancing regulatory compliance. The study contributes to the foundational development of a digital Unmanned Aircraft Traffic Management system tailored for emerging airspace users in Thailand and demonstrates potential scalability to other international regulatory contexts. Full article

(This article belongs to the Special Issue Flight Guidance and Control)

► Show Figures

Figure 1

23 pages, 5093 KB

Open AccessArticle

Reentry Trajectory Online Planning and Guidance Method Based on TD3

by Haiqing Wang, Shuaibin An, Jieming Li, Guan Wang and Kai Liu

Aerospace 2025, 12(8), 747; https://doi.org/10.3390/aerospace12080747 - 21 Aug 2025

Cited by 2 | Viewed by 1491

Abstract

Aiming at the problem of poor autonomy and weak time performance of reentry trajectory planning for Reusable Launch Vehicle (RLV), an online reentry trajectory planning and guidance method based on Twin Delayed Deep Deterministic Policy Gradient (TD3) is proposed. In view of the [...] Read more.

Aiming at the problem of poor autonomy and weak time performance of reentry trajectory planning for Reusable Launch Vehicle (RLV), an online reentry trajectory planning and guidance method based on Twin Delayed Deep Deterministic Policy Gradient (TD3) is proposed. In view of the advantage that the drag acceleration can be quickly measured by the airborne inertial navigation equipment, the reference profile adopts the design of the drag acceleration–velocity profile in the reentry corridor. In order to prevent the problem of trajectory angle jump caused by the unsmooth turning point of the section, the section form adopts the form of four multiple functions to ensure the smooth connection of the turning point. Secondly, considering the advantages of the TD3 dual Critic network structure and delay update mechanism to suppress strategy overestimation, the TD3 algorithm framework is used to train multiple strategy networks offline and output profile parameters. Finally, considering the reentry uncertainty and the guidance error caused by the limitation of the bank angle reversal amplitude during lateral guidance, the networks are invoked online many times to solve the profile parameters in real time and update the profile periodically to ensure the rapidity and autonomy of the guidance command generation. The TD3 strategy networks are trained offline and invoked online many times so that the cumulative error in the previous guidance period can be eliminated when the algorithm is called again each time, and the online rapid generation and update of the reentry trajectory is realized, which effectively improves the accuracy and computational efficiency of the landing point. Full article

(This article belongs to the Special Issue Flight Guidance and Control)

► Show Figures

Figure 1

19 pages, 5011 KB

Open AccessArticle

Vector Field-Based Robust Quadrotor Landing on a Moving Ground Platform

by Woohyun Byun, Soobin Huh, Hyeokjae Jang, Suhyeong Yu, Sungwon Lim, Seokwon Lee and Woochul Nam

Aerospace 2025, 12(7), 590; https://doi.org/10.3390/aerospace12070590 - 29 Jun 2025

Cited by 1 | Viewed by 1263

Abstract

The autonomous landing of unmanned aerial vehicles (UAVs) on moving platforms has potential applications across various domains. However, robust landing remains challenging because the detection reliability of UAVs decreases when the UAV is close to a moving platform. To address this issue, this [...] Read more.

The autonomous landing of unmanned aerial vehicles (UAVs) on moving platforms has potential applications across various domains. However, robust landing remains challenging because the detection reliability of UAVs decreases when the UAV is close to a moving platform. To address this issue, this paper proposes a novel landing strategy that ensures a high detection rate. First, a robust detectable region was established by considering the sensing range and maneuverability limitations of the UAV. Second, a vector field was designed to guide the UAV to the moving platform while remaining in a robust detectable region. Next, safe and accurate landings were achieved by considering the current velocity and vector field. The landing strategy was validated through outdoor flight experiments. A quadrotor equipped with a gimbal-mounted camera was used, and a fractal marker was attached to the moving platform for detection and tracking. When the moving platform moved at a speed of 2–4.3 m/s, the UAV successfully landed on the platform with a distance error of 0.4 m. Because of the robust detectable region and vector field, the detection was conducted with a high success rate (94.9%). Full article

(This article belongs to the Special Issue Flight Guidance and Control)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Flight Guidance and Control

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (8 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI