Neural Power-Optimal Magnetorquer Solution for Multi-Agent Formation and Attitude Control
For aerospace engineers, it provides a practical solution to reduce power consumption in satellite formation and attitude control using magnetorquers.
This paper develops a learning-based model for power-optimal current calculation in magnetorquer-based multi-agent formation and attitude control, achieving optimal performance validated through simulations and experiments.
This paper presents a learning-based current calculation model to achieve power-optimal magnetic-field interaction for multi-agent formation and attitude control. In aerospace engineering, electromagnetic coils are referred to as magnetorquer (MTQ) coils and used as satellite attitude actuators in Earth's orbit and for long-term formation and attitude control. This study derives a unique, continuous, and power-optimal current solution via sequential convex programming and approximates it using a multilayer perceptron model. The effectiveness of our strategy was demonstrated through numerical simulations and experimental trials on the formation and attitude control.