Article
Engineering, Aerospace
Pedro Orgeira-Crespo, Guillermo Rey, Carlos Ulloa, Uxia Garcia-Luis, Pablo Rouco, Fernando Aguado-Agelet
Summary: The design of a vehicle launch involves optimizing the climb path and mass distribution. This research proposes a software for separately optimizing the trajectory of a launch rocket, maximizing payload weight and global design while varying the power plant selection. The optimization algorithm is compared to real rockets and other modeling algorithms, with differences of up to 9%.
Article
Engineering, Aerospace
Brian G. Coulter, Daning Huang, Zhenbo Wang
Summary: This paper discusses the importance of integrated design frameworks covering high-fidelity disciplinary models such as aerodynamics and trajectory modeling, and introduces an energy-based problem formulation and optimization method for hypersonic vehicle design. Finally, a novel, iterative, data-driven framework is established using Bayesian optimization and machine learning to integrate these disciplinary models and successively search for the geometry that enables optimal mission performance.
JOURNAL OF AIRCRAFT
(2022)
Article
Robotics
Michael O'Connell, Guanya Shi, Xichen Shi, Kamyar Azizzadenesheli, Anima Anandkumar, Yisong Yue, Soon-Jo Chung
Summary: This study focuses on the flight control problem of UAVs in dynamic high-speed winds and proposes a learning-based approach called Neural-Fly. By incorporating pretrained representations and using domain adversarially invariant meta-learning algorithm, Neural-Fly achieves precise flight control under challenging wind conditions and provides robustness guarantees.
Article
Engineering, Marine
Zhihong Jiang, Hongyu Wu, Qingjian Wu, Yunqiang Yang, Lijie Tan, Shaoze Yan
Summary: This paper studies the motion trajectory design methods of underwater gliders for fixed-point exploration missions. Performance analysis models of the gliders are established, and the missions are divided into three categories. Two trajectory design methods are proposed based on the glider motion modes, and an optimization method is used to design the optimal motion trajectory. Numerical examples are provided to validate the methods.
Article
Engineering, Aerospace
Pureum Kim, Sang-Young Park
Summary: This study investigates the preliminary trajectory design for high-thrust missions to near-Earth asteroids (NEAs) considering distance and phase angle constraints. The results show that a constrained trajectory with a small increase in Delta v can be achieved by extending the final leg of the unconstrained reference trajectory and incorporating deep-space maneuvers. The effects of phase angle and minimum distance constraint on Delta v are also examined.
Article
Computer Science, Interdisciplinary Applications
Atticus Beachy, Harok Bae, Ian Boyd, Ramana Grandhi
Summary: By embedding multi-fidelity models in selected neurons of hidden layers, the proposed method accelerates training, reduces reliance on high-fidelity data, decreases data sampling, improves accuracy, lowers overfitting risk, and achieves robust fitting with randomly initialized weights.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Engineering, Aerospace
Laura Medioni, Yvan Gary, Myrtille Monclin, Come Oosterhof, Gaetan Pierre, Tom Semblanet, Perrine Comte, Kevin Nocentini
Summary: The increasing amount of debris in Low Earth Orbit poses challenges to the sustainability of the space environment. The current recommendations for deorbiting satellites are insufficient, and active debris removal missions are still in their early stages due to high costs. One approach to reduce costs is to remove multiple pieces of debris per mission, which requires optimizing the number of debris removed while minimizing mission time and propellant usage.
ADVANCES IN SPACE RESEARCH
(2023)
Article
Computer Science, Information Systems
Pei Pei, Shipeng Fan, Wei Wang, Defu Lin
Summary: This article proposes a modified sequential convex programming (MSCP) method to solve a highly nonlinear trajectory optimization problem for reentry vehicles. By decoupling the dynamics and convexifying the objective function, the continuous-time optimal problem is converted to an equivalent finite-dimensional sequential convex programming problem to ensure optimality of the solution and maintain feasibility with a compensation term.
Article
Engineering, Aerospace
Alessandro Zavoli, Lorenzo Federici
Summary: This paper examines the use of reinforcement learning to design low-thrust interplanetary trajectories in the presence of uncertainties and disturbances, and utilizes the Proximal Policy Optimization algorithm to train a deep neural network for optimal control policy mapping. The resulting guidance and control network produces robust trajectories and closed-loop guidance laws. Numerical results and Monte Carlo campaigns validate the proposed approach.
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2021)
Article
Engineering, Electrical & Electronic
Yao Zeng, Jianhua Tang
Summary: Unmanned aerial vehicles (UAVs) have attracted significant attention for their potential in information gathering. However, the existing data collection paradigm is insufficient for real-time gathering of information, especially in applications like smart grid. This article proposes a novel data acquisition rate model to optimize the UAV trajectory, resource allocation, and time duration in order to minimize energy consumption and mission completion time while meeting real-time processing quality requirements.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Aerospace
Jackson L. Shannon, Martin T. Ozimek, Justin A. Atchison, Christine M. Hartzell
Summary: This study introduces a new method for rapidly generating near-optimal trajectories in cislunar space using the Q-Law guidance algorithm combined with direct collocation. Through this process, powerful initial guesses for direct optimization can be provided.
JOURNAL OF SPACECRAFT AND ROCKETS
(2022)
Article
Engineering, Aerospace
Zaigui Wu, Yanbin Liu
Summary: This paper studies the optimization strategies for hypersonic vehicles using the improved pigeon-inspired optimization algorithm. It introduces Gaussian mutation to maintain diversity and avoid premature convergence, optimizes the flight control system, and designs a track controller for stability.
INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES
(2022)
Article
Engineering, Aerospace
Andrea D'Ambrosio, Troy Henderson, Alberto Clocchiatti, Daniele Mortari
Summary: This paper proposes an optimization approach and algorithm to design periodic close encounter orbits using Genetic Algorithm, and the simulations show good results.
ADVANCES IN SPACE RESEARCH
(2022)
Article
Engineering, Aerospace
Giulia Viavattene, Matteo Ceriotti
Summary: This study proposes a method based on artificial neural networks to estimate the transfer time and cost between asteroids, and optimizes rendezvous sequences through optimal control problems. The results demonstrate that the method can accurately estimate the duration and cost of low-thrust transfers in a short computational time.
JOURNAL OF SPACECRAFT AND ROCKETS
(2022)
Article
Engineering, Aerospace
Harish Saranathan, Michael J. Grant
Summary: This investigation demonstrates the use of planar rigid body dynamics in hypersonic trajectory optimization within the indirect trajectory optimization framework. The use of rigid body dynamics captures the coupling between the optimal trajectory, vehicle geometry, mass distribution, and control configuration, providing trajectories that implicitly account for the maneuverability of the vehicle. Additionally, optimal trajectories calculated using rigid body dynamics accurately reflect the drag penalties incurred during maneuvering, which is important in high-performance applications where maximizing terminal velocity is necessary. However, there is limited literature on employing rigid body dynamics in trajectory optimization, especially within the indirect methods.
JOURNAL OF SPACECRAFT AND ROCKETS
(2023)
