Developing Algorithms of Spacecraft Attitude and Orbit Control System Based on Artificial Intelligence
Researcher:
Prof. R. Tamer Mekky Ahmed
Summary of project:
Modern Techniques (MTs) of spacecraft Guidance, Navigation, and Control (GNC) include spacecraft attitude propagation, spacecraft orbit propagation, spacecraft attitude determination, spacecraft attitude estimation, spacecraft orbit estimation, spacecraft attitude control, and spacecraft orbit control. The designer of the spacecraft Attitude and Orbit Control System (AOCS) usually develops ADCS algorithms based on MTs. As model complexity increases, its accuracy increases also. But this limits greatly algorithm capability for real- time application on-board the spacecraft. The designer of AOCS may resort to scarify algorithm accuracy in order to maintain its real-time capability. Artificial Intelligence (AI) could represent a solution for this problem. Some structures of AI algorithms are nearly independent of model complexity. This enables the designer to have high accuracy of In-orbit spacecraft GNC algorithms while preserving its real-time applicability.
The objective of the project:
Conduct a survey of commonly used spacecraft attitude representing parameters.
Selection of suitable parameters representing spacecraft attitude for the current project.
Spacecraft Attitude motion modelling.
Conduct a survey of commonly used spacecraft orbit representing parameters.
Selection of suitable parameters representing spacecraft orbit for the current project.
Spacecraft Orbital Motion Modelling.
Conduct a survey on spacecraft attitude determination methods.
Selection of a suitable attitude determination method.
Conduct a survey on spacecraft attitude estimation methods.
Selection of a suitable attitude estimation method.
Conduct a survey on spacecraft orbit estimation methods.
Selection of a suitable orbit estimation method.
Conduct a survey on spacecraft attitude control algorithms.
Selection of a suitable attitude control algorithm.
Spacecraft orbit control development.
Selection of a suitable spacecraft orbit control algorithm.
Provide a survey over different AI techniques.
Selection of appropriate AI techniques to be implemented.
The most important outputs:
T.M, Habib, “Three-axis High-Accuracy Spacecraft Attitude Estimation via Sequential Extended Kalman Filtering of Single-Axis Magnetometer Measurements”, Aerospace Systems, 2023, https://doi.org/10.1007/s42401-023-00221-w.
- T.M, Habib, “Erratum for A Combined Configuration (αβ filter- TRIAD algorithm) for Spacecraft Attitude Estimation based on in-Orbit Flight Data”, Aerospace Systems, 2023, Accepted.
- T.M, Habib, “Artificial Intelligence Insights for Spacecraft Guidance, Navigation and Control: An Egyptian Viewpoint”, Council of Space Science and Remote Sensing Workshop on Space Technology and its Applications, 8 May 2023.
- T.M, Habib, “Magnetometer-Only Kalman Filter Based Algorithms for High Accuracy Spacecraft Attitude Estimation (A Comparative Analysis)”, International Journal of Robotics and Control Systems, Vol.3, No. 3, July, 2023, pp. 433-448
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National Authority for Remote Sensing & Space Sciences
NARSS is the pioneering Egyptian institution in the field of satellite remote sensing. NARSS is an outgrowth of a Remote Sensing Center, established in 1971 as an American-Egyptian joint project that was affiliated to the Egyptian Academy of Scientific Research and Technology
