Project Overview
As the GNC (Guidance, Navigation, and Control) Lead for the UCF Senior Design RTLS Rocketry Team Purple, I spearheaded the development of an innovative Return-To-Launch-Site trajectory control system. This project demonstrates the intersection of mechanical engineering principles and advanced software development.
Key Achievements
Trajectory Control Algorithm
Developed an adaptive PD control system in MATLAB for real-time course correction under variable wind conditions.
Avionics Integration
Led full-system integration of multiple sensors including GPS, IMU, barometer, magnetometer, and radio, with sophisticated calibration for environmental factors.
Simulation & Analysis
Implemented Monte Carlo analysis with 1000+ randomized trials, achieving landing accuracy within 800 ft of target.
Technical Implementation
System Architecture
- Dual-core embedded system architecture on ESP32
- Real-time sensor fusion using Kalman filtering
- Hardware-in-the-loop (HIL) testing framework
- Telemetry radio integration and SD data logging
Control System Design
- Adaptive PD control algorithm
- Wind compensation system
- Real-time trajectory optimization
- Fail-safe mechanisms and error handling
Detailed Technical Specifications
Hardware Components
-
Microcontroller:
- ESP32-WROOM-32D
- Dual-core processor up to 240MHz
- 520KB SRAM, 4MB Flash
-
Sensors:
- BNO055 9-DOF IMU
- NEO-M8N GPS Module
- BMP388 Barometric Pressure Sensor
- RFM95W LoRa Radio Module
Software Architecture
-
Real-time OS:
- FreeRTOS Task Management
- Dual-core Task Distribution
- Interrupt-driven Sensor Handling
-
Communication Protocols:
- I2C for Sensor Integration
- SPI for Radio Communication
- UART for GPS Data
Control System Implementation
Guidance Algorithm
The guidance system employs a sophisticated PD control algorithm with adaptive gains based on flight conditions:
Position Control
- Proportional Gain (Kp): 0.8 - 2.5 (adaptive)
- Derivative Gain (Kd): 0.3 - 1.2 (adaptive)
- Update Rate: 50Hz
Wind Compensation
- Real-time wind estimation using Kalman filtering
- Dynamic trajectory adjustment
- Maximum wind speed tolerance: 15 mph
Navigation System
Sensor Fusion
- Extended Kalman Filter implementation
- GPS position accuracy: ±2.5m
- Attitude estimation rate: 100Hz
- Barometric altitude resolution: ±0.5m
State Estimation
- 13-state vector tracking
- Position and velocity estimation
- Quaternion-based attitude representation
- Bias and scale factor compensation
Performance Analysis
Monte Carlo Simulation Results
- Number of trials: 1,000+
- Success rate: 92%
- Average landing accuracy: 450ft
- Maximum deviation: 800ft
System Specifications
- Control loop frequency: 50Hz
- Sensor fusion update rate: 100Hz
- Telemetry transmission rate: 10Hz
- Data logging rate: 20Hz
Key Performance Metrics
| Metric | Target | Achieved |
|---|---|---|
| Landing Accuracy | < 1000 ft | 800 ft |
| Control Response Time | < 50 ms | 20 ms |
| Wind Tolerance | 12 mph | 15 mph |
| Battery Life | 2 hours | 2.5 hours |
Testing and Validation
Hardware-in-the-Loop Testing
- Custom MATLAB simulation environment
- Real-time sensor data injection
- Performance validation under various conditions
Field Testing
- Multiple test flights conducted
- Data collection and analysis
- System refinement based on real-world performance
Safety Features
- Redundant sensor systems
- Fail-safe recovery modes
- Emergency abort capabilities
Hardware-in-the-Loop Demonstration
Watch our HIL testing system in action, demonstrating real-time sensor data processing and control system response:
About this Demonstration
This video showcases our Hardware-in-the-Loop testing environment, where we:
- Simulate flight conditions and sensor inputs
- Validate control system response in real-time
- Test edge cases and failure scenarios
- Verify system performance metrics
Project Documentation
Access the comprehensive technical documentation for the RTLS project, including detailed system architecture, validation strategies, performance analysis, and complete implementation details:
Results & Impact
- Achieved consistent landing accuracy within 800 ft across 1000 simulated trials
- Successfully implemented real-time wind compensation
- Developed reusable GNC framework for future projects
- Created comprehensive documentation for knowledge transfer