Time-Varying Model Predictive Attitude Control for Magnetically Actuated Dual-Spin Satellites

TL;DR

This paper develops and compares time-varying model predictive control strategies for magnetically actuated dual-spin CubeSats, optimizing attitude control with minimal actuation and computational effort.

Contribution

It introduces a nonlinear prediction-based MPC approach for dual-spin satellite attitude control, outperforming linear methods in constraint satisfaction and actuation minimization.

Findings

Nonlinear prediction policy achieves better constraint adherence.

Nonlinear MPC reduces control effort compared to linear methods.

The proposed approach is computationally efficient for onboard implementation.

Abstract

Attitude control hardware for small satellites is often limited in power and space availability given the importance of the science instruments they exist to transport. To mitigate this, a dual-spin stabilized satellite actuated via magnetic torque rods reduces the space and power required of the attitude control system, but may require advanced control policies. This paper explores the attitude control of a magnetically actuated dual-spin stabilized CubeSat with model predictive control using time-varying prediction dynamics. An inertial pointing objective is used as a representative mission, where the satellite is able to deviate from its nominal orientation within some allowable amount. Three time-varying MPC policies are developed and compared to ensure the system does not violate constraints while minimizing control effort. These policies include a prediction model that accounts for the orbital position of the satellite and two iterative approaches that incorporate control inputs through either propagation of the linear dynamics, or nonlinear propagation with successive linearization. Results demonstrate that the nonlinear prediction policy outperforms other prediction methods with regards to not only minimal actuation, but to constraint satisfaction as well while imparting minimal computational burden.