(Convex) Model Predictive Control for the Soft Landing Problem
This project reproduce the Powered-Descent Guidance algorithm used to solve the classical soft landing problem and run them using a Model Predictive Controller while we introduce control disturbances. There is still a lot of work to be done before we have robust Powered Descent Guidance algorithms, which means there are many areas for improvement!
A 1st version of my report is also included in the repository. An exemple video is available (attitude is made up ONLY for the purpose of the video and does not represent anything meaningful here) https://drive.google.com/file/d/1lMlodNhMEe32YmtMXmgFV3_WCog-Hp4-/view?usp=sharing.
[1] Acikmese, B., Carson, J. M., and Blackmore, L. (2013). Lossless convexification of nonconvex control bound and pointing constraints of the Soft Landing Optimal Control Problem. IEEE Transactions on Control Systems Technology, 21(6), 2104–2113. https://doi.org/10.1109/tcst.2012.2237346
[2] Carson, John M., Behcet Acikmese, and Lars Blackmore. “Lossless Convexification of Powered-Descent Guidance with Non-Convex Thrust Bound and Pointing Constraints.” Proceedings of the 2011 American Control Conference, 2011. https://doi.org/10.1109/acc.2011.5990959.
[3] Acikmese, B., and Ploen, S. R. (2007). Convex programming approach to powered descent guidance for Mars Landing. Journal of Guidance, Control, and Dynamics, 30(5), 1353–1366. https://doi.org/10.2514/1.27553