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Density Estimation for Entry guidance Problems Using Deep Learning

JOURNAL OF guidance CONTROL AND DYNAMICS 2025年第5期48卷 1042-1053页

作者： Rataczak, Jens A. Amato, Davide Mcmahon, Jay W. Univ Colorado Boulder Dept Aerosp Engn Sci Boulder CO 80302 USA Imperial Coll London Dept Aeronaut London SW7 2AZ England

The accuracy of predictor-corrector entry guidance algorithms relies heavily on the accuracy of the onboard atmospheric density model. Existing approaches, such as fading-memory filters, assume a constant bias in the density profile from the current state in the entry trajectory to the terminal condition which does not capture the geospatial variation of atmospheric density. In this work, a deep-learning approach to estimate atmospheric density profiles for use in planetary entry guidance problems is developed. A long short-term memory (LSTM) neural network is trained to learn the mapping between measurements available onboard an entry vehicle and the density profile through which it is flying. Measurements include the spherical state representation, Cartesian sensed acceleration components, and a surface-pressure measurement. Training data for the network are initially generated by performing a Monte Carlo analysis of an entry mission at Mars using the fully numerical predictor-corrector guidance (FNPEG) algorithm that uses an exponential density model, while the truth density profiles are sampled from MarsGRAM. An iterative curriculum-learning procedure is developed to refine the LSTM network's predictions for integration within the FNPEG algorithm. The trained LSTM is capable of accurately predicting both the density profile through which the vehicle will fly and reconstructing the density profile through which it has already flown. The performance of the FNPEG algorithm is assessed for three different density estimation techniques: an exponential model, an exponential model augmented with a first-order fading-memory filter, and the LSTM network. Results demonstrate that using the LSTM model results in an order of magnitude increase in terminal accuracy compared to the other two techniques when considering both noisy and noiseless measurements.

关键词： Feedforward Neural Network Planets Hypersonic Inflatable Aerodynamic Decelerator Monte Carlo Simulation Atmospheric Density Aerodynamic Coefficients guidance and navigational algorithms guidance, Navigation, and Control Systems Inertial Measurement Unit Probability Density Functions

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Impact Time Control guidance Using Output Trajectory Shaping Method

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JOURNAL OF guidance CONTROL AND DYNAMICS 2025年第4期48卷 961-967页

作者： Lee, Suwon Kim, Mingu Tekin, Raziye Kookmin Univ Dept Future Mobil 77 Jeongneung Ro Seoul 02707 South Korea Hansung Univ Div Mech & Elect Engn Seoul 02876 South Korea Roketsan Missiles Inc Tactical Missile Syst TR-06780 Ankara Turkiye

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Lyapunov guidance Vector Field-Based Waypoint Following by Unmanned Aerial Vehicles

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JOURNAL OF guidance CONTROL AND DYNAMICS 2025年第1期48卷 192-202页

作者： Harinarayana, Tammineni Krishnan, Siva Vignesh Hota, Sikha Indian Inst Technol Dept Aerosp Engn Kharagpur 721302 India

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Line-of-Sight-Constrained Multicopter Interceptability

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JOURNAL OF guidance CONTROL AND DYNAMICS 2025年第4期48卷 951-960页

作者： Yang, Kun Bai, Chenggang Quan, Quan Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

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Robust Launch Vehicle Trajectory Optimization with Stage Impact and Heat Flux Constraints

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JOURNAL OF SPACECRAFT AND ROCKETS 2023年第4期60卷 1268-1283页

作者： Swaminathan, Shriram Rajeev, U. P. Ghose, Debasish Indian Space Res Org Vikram Sarabhai Space Ctr Guidance Design Div Veli Perumathura Rd Thiruvananthapuram 695022 Kerala India Indian Space Res Org Vikram Sarabhai Space Ctr Control & Guidance Design Grp Veli Perumathura Rd Thiruvananthapuram 695022 Kerala India Indian Inst Sci Aerosp Engn Dept CV Raman Rd Bengaluru 560012 Karnataka India

A fast trajectory optimization/guidance algorithm in the presence of path constraints for a multistage launch vehicle is presented in this work. The optimization problem is to maximize the payload to be injected into a geostationary transfer orbit with constraints on argument of perigee, second-stage impact point longitude, and heat flux constraint on the third stage that flies a low-altitude trajectory. These constraints constitute a unique set of equality and inequality constraints as they are contradictory in nature. Most of the gradient-based trajectory optimization schemes require an initial guess close enough to the optimal value for assured convergence. In addition, the rate of convergence deteriorates in the presence of inequality constraints. These issues are addressed by providing a solution to the optimization problem with low sensitivity to the initial guess profiles. A self-starting optimization scheme that can generate initial guess profiles automatically from boundary conditions is the major contribution of this work. The proposed method presented in this paper also gives a methodology for real-time implementation of the optimization scheme in the onboard computer. The sensitivity to initial guess in a gradient-based optimization procedure, in the presence of inequality constraints, is clearly brought out as part of this work by studying the convergence from random sets of initial guess profiles. The real-time implementation of the algorithm is validated with various initial conditions in deterministic as well as Monte Carlo sense to establish the robustness of the algorithm.

关键词： Trajectory Optimization Vehicle Trajectories Geostationary Transfer Orbit guidance and navigational algorithms Legendre Pseudospectral Method Flight Path Angle Real-Time Optimization

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Abort guidance During Lunar Powered Descent

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JOURNAL OF guidance CONTROL AND DYNAMICS 2024年第3期47卷 394-406页

作者： Sandoval, Sergio A. Lu, Ping Hwang, John T. San Diego State Univ San Diego CA 92182 USA NASA Johnson Space Ctr Houston TX 77058 USA San Diego State Univ Dept Aerosp Engn San Diego CA 92182 USA Univ Calif San Diego Dept Mech & Aerosp Engn San Diego CA 92093 USA

During powered descent of a crewed lunar landing mission, the ability to abort and ascend into a clear pericynthion orbit is critical in case any contingency renders the landing infeasible or excessively risky. In such a case, it is incumbent upon the guidance system to determine autonomously a safe abort trajectory and the associated guidance command. To accomplish this task reliably, a novel two-phase abort guidance strategy is proposed in this paper where a pull-up maneuver redirects the velocity vector to help mitigate any ground collision risk and achieve an appropriate initial ascent condition, followed by a fuel-optimal ascent guidance algorithm to insert the spacecraft into a predefined safe orbit around the moon. Development of the pull-up guidance laws and a description of the fuel-optimal ascent guidance based on the indirect method of optimal control are presented. In-depth investigation is conducted to provide a full understanding of the validity of the abort solutions. The solutions and fuel efficiency of the proposed guidance strategy are independently verified by using a direct method of optimal control. Monte Carlo closed-loop simulations demonstrate the effectiveness and robustness of this method throughout the entire powered descent.

关键词： guidance, Navigation, and Control Systems Control Theory Solar System Moons Transversality Condition Space Missions guidance and navigational algorithms Energy Economics Propellant Flight Path Angle Powered Descent Initiation

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Urban Air Mobility guidance with Panel Method: Experimental Evaluation Under Wind Disturbances

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JOURNAL OF guidance CONTROL AND DYNAMICS 2024年第6期47卷 1080-1096页

作者： Bilgin, Zeynep Yavrucuk, Ilkay Bronz, Murat Tech Univ Munich Inst Rotorcraft & Vert Flight TUM Sch Engn & Design D-85748 Garching Germany Tech Univ Munich Inst Rotorcraft & Vert Flight TUM Sch Engn & Design D-85748 Garching Germany Univ Toulouse Ecole Natl Aviat Civile ENAC Lab Dynam SystENAC F-31400 Toulouse France

In this paper, a nature-inspired guidance algorithm based on the panel method is proposed. The panel method is a numerical tool borrowed from the aerodynamics domain to calculate the potential field of a fluid flow around arbitrarily shaped objects. The proposed algorithm has little computational load and generates guidance vectors in real time that can guide multiple vehicles through smooth and collision-free paths. Panel-method-based guidance is a promising candidate for air mobility applications in urban environments where multiple aerial vehicles are expected to operate simultaneously without colliding with architectural structures and other vehicles in the airspace. In this study, the effectiveness and feasibility of the proposed guidance method is evaluated through a test campaign conducted in Toulouse, France, using multiple quadrotors in a scaled urban environment. Furthermore, the robustness of the guidance method under wind disturbances is tested in both indoor and outdoor experiments. Experimental results suggest that the panel-method-based guidance algorithm is an effective and robust tool for real-time, collision-free guidance of multiple aerial vehicles in complex urban environments.

关键词： Urban Air Mobility guidance and navigational algorithms Quad Rotor Free Stream Velocity Airspace Fluid Flow Properties Real Time Path Planning Obstacle Avoidance

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Energy-Efficient Ring Formation Control with Constrained Inputs

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JOURNAL OF guidance CONTROL AND DYNAMICS 2023年第7期46卷 1397-1407页

作者： Ranjan, Praveen Kumar Sinha, Abhinav Cao, Yongcan Tran, Dzung Casbeer, David Weintraub, Isaac Univ Texas San Antonio Unmanned Syst Lab Dept Elect & Comp Engn San Antonio TX 78249 USA US Air Force Res Lab Control Sci Ctr Wright Patterson AFB OH 45433 USA

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Multi-Objective Robust Trajectory Design for Powered Descent and Landing

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JOURNAL OF SPACECRAFT AND ROCKETS 2024年第6期61卷 1496-1509页

作者： Calkins, Grace E. Putnam, Zachary R. Woffinden, David C. Univ Illinois Aerosp Engn Dept 104 S Wright St Urbana IL 61801 USA NASA Johnson Space Ctr GN&C Autonomous Syst Branch Houston TX 77508 USA

A robust trajectory optimization approach for guidance algorithm gain and target vector selection for powered descent and landing is developed. A genetic algorithm is used to determine optimized guidance algorithm parameters to minimize the impact of initial condition, environment, navigation, and vehicle property uncertainty on flight performance for a given sensor suite. Vehicle state uncertainties are computed efficiently using linear covariance analysis techniques. When implemented in the guidance algorithm, the optimized gains and target vectors shape a trajectory that has more favorable conditions for a given navigation sensor suite, resulting in improved flight performance. As a demonstration of this method, the optimized guidance parameters are found for a multiphase trajectory from powered descent initiation to touchdown for a robotic lunar landing mission. Single-objective optimization results demonstrate a reduction in uncertainty and an improvement in nominal performance. Multi-objective optimization results showing the tradeoff between terminal position uncertainty and total propellant usage are presented for multiple sensor suite compositions. Further, guidance parameters selected using the developed robust trajectory design approach may enable acceptable flight performance with fewer and/or lower-quality sensors. The resulting Pareto fronts present the optimal trade space early in the mission design process to enable informed decision-making.

关键词： Spacecraft Design Propellant Sensors Powered Descent Initiation guidance and navigational algorithms Genetic Algorithm Trajectory Optimization Space Missions Terrain Relative Navigation

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Rethinking Propellant-Optimal Powered Descent guidance

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JOURNAL OF guidance CONTROL AND DYNAMICS 2024年第10期47卷 2016-2028页

作者： Lu, Ping Davami, Christopher San Diego State Univ Dept Aerosp Engn San Diego CA 92182 USA

The propellant-optimal powered descent solution requires a bang-bang thrust magnitude profile that switches instantaneously between the upper and lower bounds of the engine thrust. Implementing a bang-bang thrust pattern for guidance can be challenging for the engine and may cause practical and operational difficulties. Motivated by the observation that excellent propellant performance does not appear to be predicated on necessarily having a bang-bang thrust structure, a new powered descent guidance method is proposed in this work. The foundation lies in a propellant-optimal problem in which the thrust magnitude is parameterized by a user-prescribed continuous function of time. In particular, constant and linear functions are considered. The solution determines the optimal thrust direction, time of flight, and design parameters defining the thrust function. An indirect-method-based guidance algorithm is developed to solve this problem rapidly and reliably. Substantial evidence is provided to demonstrate that the solutions proposed in this paper in general yield a propellant consumption very close to that of the optimal bang-bang solution. Given its comparable propellant performance, implementability, and robustness, this paper makes a strong case that the proposed propellant-optimal powered descent guidance approach is preferred to the long-standing bang-bang guidance approach.

关键词： guidance and navigational algorithms Powered Descent guidance Soft Landing guidance Spacecraft guidance Propellant-Optimized Autonomous Spacecraft Entry, Descent and Landing Optimal Control Problem

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