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Optimization of attitude control with RACS using Model Predictive Control algorithm: A Comparative Analysis of MPC and QFR

Federico Avalle

Optimization of attitude control with RACS using Model Predictive Control algorithm: A Comparative Analysis of MPC and QFR.

Rel. Elisa Capello, Fabio Faliero. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Aerospaziale, 2024


The state of the art in spacecraft attitude control is constantly evolving, seeking solutions aimed at meeting mission requirements while enhancing the robustness and stability characteristics of controllers. Within this context, the following thesis project is situated exploring, in the field of attitude control performed with RACS (Roll and Attitude Control System), an alternative to the classical and established QFR (Quaternion Feedback Regulator) approach through the application of an optimizer that exploits the application of the MPC (Model Predictive Control) method aiming at minimizing propellant consumption and number of thrusters activations, while simultaneously managing to meet several constraints, first and foremost that of reference thresholds (a constraint that for the types of maneuvers in which high pointing accuracy is required, becomes an additional term within the cost function). In addition to a comparison between the two types of controllers mentioned above, the discussion will cover an examination of the development of the three-degrees-offreedom simulator representing as closely as possible to reality the system consisting of the M-10, the third stage of AVIO S.p.a.’s Vega-E launcher, on which the RACS system is installed with a configuration involving two clusters of 4 thrusters each. The study, moreover, is focused on characteristic in missions maneuvers performed by the launcher using a step-by-step approach: starting from simple single-axis correction, proceeding with BBQ mode control with constant angular velocity ending with the more generic three-axis stabilization, all maneuvers with the main engine off focusing only on rotational dynamics. The results obtained, compared with QFR control, validated by nominal simulations on the system without simplifications, are very encouraging, highlighting the peculiarities of the approach with Model Predictive Control, which in contrast to the controller with which the comparison is made allows minimizing the number of activations and propellant consumption.

Relators: Elisa Capello, Fabio Faliero
Academic year: 2023/24
Publication type: Electronic
Number of Pages: 89
Additional Information: Tesi secretata. Fulltext non presente
Corso di laurea: Corso di laurea magistrale in Ingegneria Aerospaziale
Classe di laurea: New organization > Master science > LM-20 - AEROSPATIAL AND ASTRONAUTIC ENGINEERING
Aziende collaboratrici: AVIO SPA
URI: http://webthesis.biblio.polito.it/id/eprint/31231
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