Game theory applied to energy optimal satellite attitude control
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Project and Master Subjects 2024-2025
- Improving Images for Climate Action
- Every Variable Everywhere All at Once
- Protecting Water Resources through Machine Learning and Hyperspectral Imaging in Remote Sensing CubeSats
- More Effective Earth Observation for Climate Action Through Learned Data Compression in CubeSats
- Mitigating Camera Artifacts in HYPSO Data for Improved Climate Monitoring
- Characterization of High-resolution Spectral Imager
- A Foundational Unmixing Model for the HYPSO satellites
- Hyper/Multispectral image fusion with HYPSO-2
- Game theory applied to energy optimal satellite attitude control
- Mu-analysis for agile satellite attitude control maneuvers
- Randomized optimization applied to super-agile satellite operations
- Modelling super-agile satellite operations for optimization
- Enabling high-accuracy HYPSO image georeferencing by high-accuracy satellite pose estimation through postprocessing of satelitte sensor data
- High-accuracy attitude determination of Earth observation satellites
- Agile Earth Observation Satellite simulation studies
- Multi-angle image analysis and what we can learn about the atmosphere
- GNSS-R: Simulator design of a GNSS-Reflectometry small satellite
- GNSS-R: GNSS jamming and spoofing source localization from a small satellite
- GNSS-R: Maritime Surveillance using GNSS-Reflectometry
- Past Projects
Game theory applied to energy optimal satellite attitude control
Project description
This project is about developing and applying game theory methodology for satellite attitude control maneuvers. Energy is a finite resource in space and a vital part of making satellites achieve their objectives. For satellites where the attitude determines the power gained by the satellite, which is the case for a vast majority of satellites, attitude control plays an important role in the success of the mission. However, other pointing requirements can be competing with the objective of simply gaining enough energy: the satellite could for example need to point to a target area to take an image or to downlink data to a suitable ground station. This is where this project proposal comes in: the goal is to use game theory, a mathematical theory showing how competing interests work with each other, to find good, or even optimal, control solutions.
Impact of this project
Space technology plays a critical role in achieving 40% to 50% of the UN Sustainable Development Goals. The NTNU SmallSat Lab's HYPSO satellites, launched in 2022 and with a successor planned, utilize hyperspectral imagers to capture detailed information beyond the visible. This data allows us to detect and monitor water bodies like oceans, fjords, and lakes, including vital yet potentially harmful algae. The HYPSO satellites also contribute to climate change studies by imaging the Arctic region. Data from the HYPSO satellites play a role in achieving Climate Action, Preserving Life Below Water, and ensure access to Clean Water and Sanitation. The work in this project will focus on energy optimal attitude maneuvers, which means the outcome of this project can have ramifications beyond improving the gathering of HYPSO data, as the work would be applicable to most Earth observation satellites.
Tasks in this project
- Conduct a comprehensive literature review on game theory and its uses in control and in satellite attitude control .
- Develop and investigate new methods suited for this problem .
- Implement and compare the proposed solution with recently published solutions based on numerical optimal control.
Who we are looking for
We are seeking a highly motivated final year student in Cybernetics and Robotics with interest for control and mathematics. Experience from subjects such as TTK4150 (Nonlinear control systems) and/or TTK4190 (Guidance, Navigation and Control of Vehicles) will be beneficial for the student in this project. The project will be adapted to the student's goals and background.
How we work
The student will be part of the NTNU SmallSat lab, a lab which typically hosts 10-20 master's student per semester. As this project thesis would be a collaboration with Imperial, interaction with the research group in London would be expected by the student.
Supervisors
Jan Tommy Gravdahl (main supervisor, NTNU), Bjørn Andreas Kristiansen (NTNU), Thulasi Mylvaganam (Imperial College, London) .
For more information about the project or to show your interest, contact Bjørn Andreas Kristiansen at bjorn.a.kristiansen@ntnu.no.