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

TL;DR

The paper tackles rest-to-rest spacecraft attitude maneuvers under pointing constraints and actuator limits. It develops a guided APF framework to generate a feasible reference trajectory and a boundary-layer sliding mode controller to track it, with closed-form gain expressions derived via Lyapunov analysis. Robustness is assessed through mu-analysis and Monte Carlo simulations on a high-fidelity 3-DOF attitude model with a pyramidal four-wheel cluster; results show effective constraint satisfaction and bounded quaternion tracking errors. The approach demonstrates practical viability for space missions, highlighting its capacity to handle uncertainties, disturbances, and actuator saturations in realistic operating conditions.

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.

Figures (16)

• Figure 1: Pyramidal cluster of RWs app13106026
• Figure 2: Momentum (torque) sphere inscribed in the polyhedron of the momentum (torque) envelope.
• Figure 3: Spacecraft scheme with pointing constraint.
• Figure 4: Decrease of $\hat{\theta}$ with respect to $\underline{\theta}$ due to different number of forbidden zones $N$.
• Figure 5: Increase of $\theta_{\text{min}}$ with respect to $\underline{\theta}$ due to different number of forbidden zones $N$.

Theorems & Definitions (13)

• Definition 1
• Lemma 1: Theorem 4.2 in khalil2002nonlinear
• Lemma 2: Theorem 4.2 in bhat
• Proposition 1
• proof
• Corollary 1
• proof
• Remark 1
• Proposition 2
• proof