Attitude and Orbit Control Systems

Wie, Bong; Lappas, Vaios; Gil-Fernández, Jesús

doi:10.1007/978-3-642-41101-4_12

Cited by 6 publications

(3 citation statements)

References 18 publications

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“…In the field of space exploration, autonomous vision-based spacecraft (S/C) navigation is one key area with the potential of greatly benefiting from DNN-based (Deep Neural Network) estimation methods. Cameras are rapidly becoming the preferred sensor for autonomous rendezvous thanks to the introduction of compact and lightweight passive optical sensors as feasible onboard instruments [1]. Additionally, vision-based techniques have been used in-flight for inertial orbit determination tasks [2].…”

Section: Socmentioning

confidence: 99%

Deep Learning-based Spacecraft Relative Navigation Methods: A Survey

Song,

Rondao,

Aouf

2021

Preprint

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Autonomous spacecraft relative navigation technology has been planned for and applied to many famous space missions. The development of on-board electronics systems has enabled the use of vision-based and LiDAR-based methods to achieve better performances. Meanwhile, deep learning has reached great success in different areas, especially in computer vision, which has also attracted the attention of space researchers. However, spacecraft navigation differs from ground tasks due to high reliability requirements but lack of large datasets. This survey aims to systematically investigate the current deep learning-based autonomous spacecraft relative navigation methods, focusing on concrete orbital applications such as spacecraft rendezvous and landing on small bodies or the Moon. The fundamental characteristics, primary motivations, and contributions of deep learningbased relative navigation algorithms are first summarised from three perspectives of spacecraft rendezvous, asteroid exploration, and terrain navigation. Furthermore, popular visual tracking benchmarks and their respective properties are compared and summarised. Finally, potential applications are discussed, along with expected impediments.

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Section: Socmentioning

confidence: 99%

Deep Learning-based Spacecraft Relative Navigation Methods: A Survey

Song,

Rondao,

Aouf

2021

Preprint

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“…In the field of space exploration, autonomous vision-based spacecraft (S/C) navigation is one key area with the potential of greatly benefiting from DNN-based (Deep Neural Network) estimation methods. Cameras are rapidly becoming the preferred sensor for autonomous rendezvous thanks to the introduction of compact and lightweight passive optical sensors as feasible onboard instruments [2]. Additionally, vision-based techniques have been used in-flight for deep space navigation tasks [3].…”

Section: Introductionmentioning

confidence: 99%

Deep learning-based spacecraft relative navigation methods: A survey

2022

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“…Today’s spacecraft technology and systems architecture are getting sophisticated and contain redundant multi-axis actuator systems with multiple momentum exchange devices such as the thrusters, magnetorquers, control moment gyros and reaction wheels for three-axis attitude control (Wie et al , 2014). In these systems, the reaction wheels and magnetorquers in small spacecraft, and the control moment gyros and thrusters in large spacecraft are commonly used as the main actuators to perform slew maneuvers and to compensate for external disturbance torques.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy Jacobian control of spacecraft combined attitude and Sun tracking system

Chak

Varatharajoo

Assadian

2020

AEAT

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Purpose The paper aims to address the combined attitude control and Sun tracking problem in a flexible spacecraft in the presence of external and internal disturbances. The attitude stabilization of a flexible satellite is generally a challenging control problem, because of the facts that satellite kinematic and dynamic equations are inherently nonlinear, the rigid–flexible coupling dynamical effect, as well as the uncertainty that arises from the effect of actuator anomalies. Design/methodology/approach To deal with these issues in the combined attitude and Sun tracking system, a novel control scheme is proposed based on the adaptive fuzzy Jacobian approach. The augmented spacecraft model is then analyzed and the Lyapunov-based backstepping method is applied to develop a nonlinear three-axis attitude pointing control law and the adaptation law. Findings Numerical results show the effectiveness of the proposed adaptive control scheme in simultaneously tracking the desired attitude and the Sun. Practical implications Reaction wheels are commonly used in many spacecraft systems for the three-axis attitude control by delivering precise torques. If a reaction wheel suffers from an irreversible mechanical breakdown, then it is likely going to interrupt the mission, or even leading to a catastrophic loss. The pitch-axis mounted solar array drive assemblies (SADAs) can be exploited to anticipate such situation to generate a differential torque. As the solar panels are rotated by the SADAs to be orientated relative to the Sun, the pitch-axis wheel control torque demand can be compensated by the differential torque. Originality/value The proposed Jacobian control scheme is inspired by the knowledge of Jacobian matrix in the trajectory tracking of robotic manipulators.

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Attitude and Orbit Control Systems

Cited by 6 publications

References 18 publications

Deep Learning-based Spacecraft Relative Navigation Methods: A Survey

Deep Learning-based Spacecraft Relative Navigation Methods: A Survey

Deep learning-based spacecraft relative navigation methods: A survey

Adaptive fuzzy Jacobian control of spacecraft combined attitude and Sun tracking system

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