Spacecraft Attitude Dynamics

Semi-analytical attitude propagation for earth orbiting objects Irene Cavallari, Jinglang Feng, Massimiliano Vasile This paper presents the development of a semi-analytical theory for the long-term propagation of the attitude motion of Earth-orbiting objects with arbitrary shape. The attitude dynamics includes the effects of gravity-gradient, residual magnetic, and light-pressure torques. The equations of motion are expressed in Sadov variables. The equations of motion are averaged over the Sadov angles and the orbital mean anomaly and a combination of Lie transformations is applied to transform from non-averaged to mean attitude variables. It will be shown how this technique can be used to estimate the approximation error and improve the accuracy of the averaged solution. Furthermore, we introduce an alternative set of variables, that removes one of the singularities in the formulation in Sadov variables. The results of the numerical tests demonstrate that the proposed semi-analytical theory, provides a good balance between accuracy and computational cost. Free open access version. Aerospace Centre of Excellence

Simulating an Extended Kalman Filter (EKF) for Satellite Attitude Estimation Attitude Determination & Control Systems (ADCS) rely heavily on robust state estimation. One of the most widely used algorithms in flight is the Extended Kalman Filter (EKF), which fuses noisy sensor measurements to estimate spacecraft attitude and gyro bias. In this simulation, I modeled a satellite rotating with a small angular velocity vector and equipped with Gyroscope (with bias + Gaussian noise) and Star Tracker (providing noisy quaternion measurements). The EKF loop was implemented in Python: 1️⃣ Prediction step → Propagates the attitude quaternion using gyro data (bias-corrected). 2️⃣ Update step → Corrects the estimate with star tracker quaternions. 3️⃣ Bias estimation → Gyro bias is estimated alongside the quaternion state. #cubesat #ADCS #stateestimation #satellite #nanosatellite #aerospace #controlsystem #DSP #orbitalmeachanics #orbits #spacetech #python

This video illustrates my Simulink-based simulation where a satellite orbits Earth, dynamically responding to real-time commands derived from an MPU6050 sensor. As I manipulate the sensor, the satellite's attitude is adjusted accordingly, reflecting a real-time control loop between the ground station and the satellite's onboard control systems. Key Features of the System: MPU6050 Sensor: Provides real-time orientation data as the input from the ground station. Kalman Filter: Applied to filter and refine the attitude estimation, ensuring high accuracy despite sensor noise. Four Variable speed control moment gyroscopes (VSCMGs) : Configured in a pyramidal arrangement, these generate the required torques to precisely follow the control commands. Hardware-in-the-Loop Simulation: The system is tested using real-time data, bridging the gap between theory and practical implementation. This project demonstrates the potential of combining hardware simulation with advanced control systems for satellite operations, particularly in the context of real-time attitude control and dynamic response.