Avionics-Propulsion-Landers-GT/MonopropUAV
Feb 2026 – Feb 2026
1 Month active
Languages Used
Python
Technical Skills
Python programmingcontrol systemsmodel predictive controlrocket dynamics simulation
ajaymuru26
PROFILE
Ajaymuru26
Ajay Murugappa developed a sensor fusion-based rocket dynamics simulation for the Avionics-Propulsion-Landers-GT/MonopropUAV repository, focusing on enhancing trajectory prediction and thrust management. Leveraging Python, he integrated modular rocket physics—incorporating thrust and drag calculations—into a real-time simulation framework. Ajay implemented a Model Predictive Controller to optimize control responses, enabling faster and more accurate decision-making within the propulsion stack. His work established a reusable foundation for real-time optimization and automated validation, directly supporting safer and more efficient flight operations. The project demonstrated depth in control systems and model predictive control, addressing complex dynamics modeling challenges in rocket propulsion systems.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,414,508
Activity Months1
Your Network
22 peopleShared Repositories
22
Work History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for Avionics-Propulsion-Landers-GT/MonopropUAV: Delivered sensor fusion-based rocket dynamics simulation with a Model Predictive Controller (MPC) to enhance trajectory prediction and thrust management. Implemented modular rocket physics integration (thrust and drag) and dynamics modeling, paired with MPC to optimize control responses. This work strengthens flight safety and efficiency by enabling more accurate predictions and faster decision-making within the propulsion stack. Established a reusable framework for real-time optimization and automated validation, with integration aligned to the MonopropUAV subsystem. Commit referenced: cc06dd0f56f94f481531e15baae292d04ea22ebe.
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for Avionics-Propulsion-Landers-GT/MonopropUAV: Delivered sensor fusion-based rocket dynamics simulation with a Model Predictive Controller (MPC) to enhance trajectory prediction and thrust management. Implemented modular rocket physics integration (thrust and drag) and dynamics modeling, paired with MPC to optimize control responses. This work strengthens flight safety and efficiency by enabling more accurate predictions and faster decision-making within the propulsion stack. Established a reusable framework for real-time optimization and automated validation, with integration aligned to the MonopropUAV subsystem. Commit referenced: cc06dd0f56f94f481531e15baae292d04ea22ebe.
February 2026
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Python programmingcontrol systemsmodel predictive controlrocket dynamics simulation
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