Implementation of a Kalman Filter-Based Rocket Direction Control System Using ESP Microcontroller

Abstract

This paper presents a simple and low-cost rocket orientation control system using the ESP8266 microcontroller and an MPU6050 sensor. The system measures tilt angles (pitch and roll) and uses a Kalman filter to reduce noise and fuse accelerometers and gyroscope data. Based on the filtered data, servo motors adjust the fins to keep the rocket stable during flight. The system was tested at around 50 Hz update rate and showed smoother and more reliable results compared to raw sensor data. This work helps students and researchers understand practical control using low-cost sensors. This project helps understand how microcontrollers can be used for control applications in rockets.

Introduction

Rocket flight stability can be disrupted by wind, vibration, or environmental changes. To maintain proper orientation, sensors and control systems are required. This project uses an MPU6050 sensor (accelerometer + gyroscope) with an ESP8266 microcontroller to stabilize a rocket via servo-controlled fins. Raw sensor data are noisy and prone to drift, so a Kalman Filter is applied to produce accurate pitch and roll angles, enabling smooth, real-time stabilization.

System Components:

• Sensor: MPU6050 (3-axis accelerometer and gyroscope)

• Controller: ESP8266 microcontroller

• Actuators: Four SG90 servo motors for fins

• Software: Arduino IDE with Kalman Filter library

Methodology & Operation:

1. Sensor Initialization & Calibration: ESP8266 communicates with MPU6050 via I²C; gyroscope bias is corrected.

2. Data Acquisition: Accelerometer measures tilt; gyroscope measures angular velocity.

3. Kalman Filter: Fuses accelerometer and gyroscope data to reduce noise and drift, producing smooth, accurate orientation angles.

4. Angle Mapping & Servo Control: Filtered angles are constrained to ±45°, mapped to servo range (0–180°), smoothed, and used to actuate fins.

5. Closed-Loop Feedback: The process runs continuously at ~50 Hz, maintaining stable rocket orientation.

Results & Validation:

• Kalman Filter significantly reduced sensor noise and stabilized angle measurements.

• Servo response became fast and smooth, correcting tilt within ~0.5 seconds.

• System achieved stable control compared to unfiltered raw sensor data.

Advantages of ESP8266-Based Design:

• Low-cost, lightweight, low-power 32-bit processor.

• Built-in Wi-Fi, PWM capability for servo control.

• Easy programming via Arduino IDE with strong community support.

• Demonstrates that affordable microcontrollers can perform reliable real-time stabilization for aerospace applications.

Conclusion

The system successfully demonstrated how ESP8266 and MPU6050 can be used for stabilizing a rocket model. The Kalman filter helped in getting smooth angle readings, which improved control accuracy. The design is simple, cost-effective, and suitable for student-level aerospace projects. This work also gave a better understanding of how sensors, filters, and microcontrollers can work together for real-time control. It can be further improved by adding wireless data monitoring or testing it on a larger rocket model in future.

References

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Copyright

Copyright © 2025 Dharmana Kavitha, Mrs. Samrajam Jyothula. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.