Lunar-lander-robust-trajectory-tracking

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📌 Overview

In this Python project, we implement robust control laws for the control of a lunar lander subject to significant disturbances and model uncertainties. This project provides dynamical simulations, performance comparison and graphic visualization.

🚀 System dynamic description

• TVC-controlled (thrust vector control) landing gear
• 2D modeling

State variables:

• $x$: horizontal position of the landing gear
• $z$: vertical position of the landing gear
• $\theta$: pitch angle of the module body
• $m$: total mass (vehicle + fuel)
• $I$: moment of inertia about pitch

Control variables:

• $\delta$: nozzle steering angle
• $\eta$: mass flow rate at the nozzle outlet

Dynamic equations:

$$ \begin{bmatrix} \dot{x} \\ \dot{z} \\ \dot{V}_x \\ \dot{V}_z \\ \dot{\theta} \\ \dot{\omega} \\ \dot{m} \\ \dot{I} \end{bmatrix} = \begin{bmatrix} V_x \\ V_z \\ \frac{1}{m} \eta g_0 I_{spv} \cos(\theta+\delta)\\ -\frac{1}{m} \eta g_0 I_{spv} \sin(\theta+\delta) + g \\ \omega \\ -\frac{1}{I} \eta g_0 I_{spv} l_q \cos(\theta+\delta) \\ -\eta \\ -l_I^2\eta -g \end{bmatrix} $$

📊 Controllers Implemented:

• PID
• Feedback linearization

📈 Visualize Results

• Tracking second order trajectory using feedback linearization under parameter uncertainties :

How to use it

1. Run the main script main_prog.py on your favorite Python interpreter.

🤝 Contributing

Contributions are welcome!

Future improvements could include:

• SMC and NMPC implementations
• Better controller tuning
• Robustness assessment
• More detailled Readme

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