Augmented Model Predictive Control: A Balance between Satellite Agility and Computation Complexity

TL;DR

This paper introduces an augmented-MPC control strategy for agile earth observation satellites, balancing high responsiveness with computational efficiency through a novel formulation validated by simulations and experiments.

Contribution

It presents a new augmented-MPC method that combines nonlinear MPC performance with linear MPC simplicity for satellite control.

Findings

The augmented-MPC achieves high agility with reduced computational load.

Numerical simulations demonstrate improved control performance.

Physical experiments confirm the method's feasibility in real-world scenarios.

Abstract

Agile earth observation satellites employ multiple actuators to enable flexible and responsive imaging capabilities. While significant advancements in actuator technology have enhanced satellites' torque and momentum, relatively little attention has been given to control strategies specifically tailored to improve satellite agility. This paper provides a comparative analysis of different Model Predictive Control (MPC) formulations and introduces an augmented-MPC method that effectively balances agility requirements with hardware implementation constraints. The proposed method achieves the high-performance characteristics of nonlinear MPC while preserving the computational simplicity of linear MPC. Numerical simulations and physical experiments are conducted to validate the effectiveness and feasibility of the proposed approach.