Artificial Potential Field and Sliding Mode Control for Spacecraft Attitude Maneuver with Actuation and Pointing Constraints

TL;DR

This paper presents a novel control strategy combining Artificial Potential Field and Sliding Mode Control to achieve spacecraft attitude reorientation while respecting pointing and actuation constraints, uncertainties, and disturbances.

Contribution

It introduces explicit gain formulas for APF/SMC control, enhancing robustness and avoiding iterative tuning in constrained spacecraft attitude maneuvers.

Findings

Control strategy effectively handles actuation and pointing constraints.

Robustness confirmed through Monte Carlo simulations.

Explicit gain formulas improve practical implementation.

Abstract

This study investigates the combination of guidance and control strategies for rigid spacecraft attitude reorientation, while dealing with forbidden pointing constraints, actuator limitations, and system uncertainties. These constraints arise due to the presence of bright objects in space that may damage sensitive payloads onboard the spacecraft, and the risk that actuator saturations may compromise closed-loop system stability. Furthermore, spacecraft attitude dynamics are typically affected by parametric uncertainties, external disturbances, and system nonlinearities, which cannot be neglected. In this article, the problem of spacecraft reorientation under pointing and actuation constraints is addressed using a strategy that combines Artificial Potential Field (APF) and Sliding Mode Control (SMC). A rigorous Lyapunov-based analysis yields closed-form expressions for APF/SMC gains, providing explicit mathematical formulas for gain values without the need for iterative computations. These expressions account for angular velocity and control torque limitations, external disturbances, and inertia uncertainties. The robustness of the proposed control strategy is demonstrated through Monte Carlo simulations using a high-fidelity attitude dynamics simulator. Additionally, mu-analysis is employed to assess local stability properties and quantify robustness margins. The results confirm the practical feasibility of the proposed method in real-world space scenarios, highlighting its effectiveness in uncertain and constrained environments.