
Satellite attitude control systems require real-time validation of stability under parametric uncertainty and environmental perturbations. Classical methods based on Linear Matrix Inequalities (LMIs) are computationally prohibitive for embedded deployment, requiring minutes of computation per validation. This paper introduces a spectral guardian based on the hdzme001d bound—an algebraic, optimization-free stability criterion—integrated with quaternion-based attitude dynamics. The guardian evaluates system stability in under 1 ms, enabling real-time adaptive control with preventive gain adjustment. Simulations of a 6U CubeSat performing a 30° slew maneuver under orbital perturbations (aerodynamic drag, solar radiation pressure, gravity gradient, magnetic torque) demonstrate that the guardian maintains pointing accuracy < 0.1° with only 23 interventions over 160 seconds, while LMI-based validation would require 142 ms per check—exceeding the 20 ms control cycle budget. Monte Carlo analysis over 1000 random perturbations confirms zero false negatives and 99.7% compliance. The method is suitable for CubeSats, small satellites, and formation flying missions where computational resources are constrained.
Spectral stability analysis 5. Real-time validation 6. CubeSat simulations 7. Orbital perturbations 8. Embedded control systems, Adaptive gain adjustment, Monte Carlo robustness, Satellite attitude control, Robust stability bounds, Quaternion dynamics, Spectral stability analysis 5. Real-time validation 6. CubeSat simulations 7. Orbital perturbations 8. Embedded control systems, Adaptive gain adjustment, Monte Carlo robustness
Spectral stability analysis 5. Real-time validation 6. CubeSat simulations 7. Orbital perturbations 8. Embedded control systems, Adaptive gain adjustment, Monte Carlo robustness, Satellite attitude control, Robust stability bounds, Quaternion dynamics, Spectral stability analysis 5. Real-time validation 6. CubeSat simulations 7. Orbital perturbations 8. Embedded control systems, Adaptive gain adjustment, Monte Carlo robustness
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