Project description

Mu-analysis is a type of robustness analysis typically deployed when there is uncertainty in the system. The method is a way of analyzing the uncertainty in the system: if you identify the magnitude of uncertainty your system can handle, here in frequency, you can say something about the robustness of the system. Typical applications of this method in the space sector have been to ensure that high-performance pointing systems, such as the recently launched space telescopes, can accomplish the required science objectives despite various types of vibrations in the spacecraft structure. The objective of this project would be to look at this type of method applied to highly agile satellite maneuvers, working towards merging the precision-benefits from mu-analysis with the agility we want from our satellite maneuvers.

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 can make an impact beyond the three sustainable development goals mentioned previously, as the work related to robustness would be applicable to most Earth observation satellites, in particular high-performance pointing systems.

Tasks in this project

• Conduct a comprehensive literature review on mu-analysis and the current state-of-the-art, including the current work being done on this in the European space industry .
• Develop and investigate new methods suited for this problem .
• Implement and show how the new methods compare to the state-of-the-art .

Who we are looking for
We are seeking a highly motivated final year student in Cybernetics and Robotics with interest for control. Experience from subjects such as 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.

Supervisors

Jan Tommy Gravdahl (main supervisor, NTNU), Bjørn Andreas Kristiansen (NTNU).

For more information about the project or to show your interest, contact Bjørn Andreas Kristiansen at bjorn.a.kristiansen@ntnu.no.