This article addresses the challenge of controlling both attitude and orbit in satellites using an integrated approach. Traditional designs typically employ separate systems for orbit control, such as thrusters, and attitude control, such as reaction wheels, which can complicate control strategies. We propose a novel method that utilizes a nonlinear control strategy optimized by a Genetic Algorithm (GA) in conjunction with Model Predictive Control (MPC), focusing on managing both attitude and orbit simultaneously. By explicitly accounting for the coupled dynamics of attitude and orbit, this approach enhances the efficiency of the control system. The real-time implementation of GA-based MPC allows responsive control that overcomes the limitations of the conventional on-off methods which are slow in reaching desired setpoints. We also design a new test platform to evaluate the performance of the attitude and orbit control system (AOCS). The results demonstrate that the proposed control algorithm effectively steers the satellite to the desired setpoints for both attitude and orbit, highlighting the feasibility and effectiveness of the proposed GA-based MPC approach.
Ga-based MPC for satellite’s attitude and orbit control
Discov Appl Sci
Discover Applied Sciences ; 7 , 8
21.07.2025
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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