CubeSat ADCS: Estimation and Control

This repository contains a demonstrator project for an Attitude Determination and Control System (ADCS) applied to a CubeSat. The goal is to provide a learning and portfolio project that showcases skills in dynamics modeling, control, and sensor fusion, relevant for aerospace and defense applications.

This project has not been updated in a long time and latest updates are still to be validated and pushed

---

Features

• CubeSat rotational dynamics simulation (Euler’s equations)
• PD controller for attitude stabilization
• Simulated sensors: gyroscope, magnetometer, sun sensor
• Extended Kalman Filter (EKF) for sensor fusion and state estimation
• Visualization of results: angles, angular velocities, estimation errors

---

Usage

1. Dynamics and Control Simulation

python adcs_simulation.py

Outputs:

• Attitude dynamics with external disturbances
• Stabilization using PD control
• Plots of true angles vs controlled response

2. Attitude Estimation with EKF

python ekf_estimation.py

Outputs:

• Simulated noisy sensor measurements
• EKF estimates of angle and angular velocity
• Comparison plots (true vs estimated states)

---

Repository Structure

cubesat-adcs/
│
├── adcs_simulation.py      # CubeSat dynamics + PD controller
├── ekf_estimation.py       # EKF-based attitude estimation
│
├── plots/                  # Saved figures from simulations
├── docs/                   # Background notes and references
└── README.md

---

Example Results

PD Control

• CubeSat stabilizes to target attitude despite disturbances
• Response plotted as angle vs time

EKF Estimation

• EKF successfully tracks true angle and angular velocity
• Estimation error decreases over time despite sensor noise

---

Roadmap

• Add advanced controllers (LQR, Sliding Mode)
• Include realistic perturbations (gravity gradient, aero, solar pressure)
• Full CubeSat mission simulation

---

Goals

With this personal project I try to demonstrate practical skills in nonlinear dynamics modeling, real-time control laws, sensor fusion with Kalman filtering, documentation and reproducibility of simulations.

It serves as a portfolio project for applications in aerospace and defense industries.

---

References

• Markley & Crassidis, Fundamentals of Spacecraft Attitude Determination and Control
• Schaub & Junkins, Analytical Mechanics of Space Systems
• Simon, Optimal State Estimation

---

Contact

Created by Riccardo Legnini.
Feel free to connect via LinkedIn or open an issue for discussion!