Recursive Adaptive Control of CubeSat Attitude via Multi-Modal Sensor Fusion and HyperScore-Driven Optimization

**Abstract:** This paper introduces a novel approach to CubeSat attitude control utilizing recursive adaptive control (RAC) algorithms enhanced by multi-modal sensor fusion and a HyperScore-driven optimization engine. Addressing the limitations of traditional PID controllers in dynamically changing orbital environments and resource-constrained CubeSat platforms, our system achieves significantly improved attitude stability and accuracy while minimizing power consumption. The core innovation lies in the integration of a HyperScore evaluation framework that dynamically weights sensor data and control parameters based on real-time performance, fostering optimal adaptation and resilience against disturbances. This system is readily commercializable for a wide range of CubeSat applications, including Earth observation, scientific payload stabilization, and formation flying.