Optimization of Field Tuning Configuration of Flight Controller KK2.1.5 Based on IMU Sensor Integration on a Quadcopter

Abstract

This study presents the optimization of the field tuning configuration of the KK2.1.5 flight controller based on IMU sensor integration on a quadcopter platform to improve flight stability, maneuverability, and control responsiveness. The research employed an experimental method involving direct outdoor flight testing combined with incremental adjustment of Proportional–Integral (PI) control parameters, including roll, pitch, yaw, and self-level gains. The KK2.1.5 flight controller integrated with the MPU6050 IMU sensor was utilized to provide real-time attitude estimation through gyroscope and accelerometer measurements. The experimental evaluation focused on several flight performance parameters, namely hovering stability, roll maneuver accuracy, pitch maneuver accuracy, yaw response accuracy, altitude stabilization, response time, oscillation level, drift deviation, hovering accuracy, and control responsiveness. Ten repeated experimental trials were conducted to analyze the effectiveness of the tuning optimization process. The results demonstrated significant improvements in all flight performance indicators after iterative tuning adjustments. Hovering stability increased from 91.2% to 98.7%, while altitude stabilization improved from 90.5% to 98.3%. Furthermore, response time decreased from 1.84 s to 0.85 s, oscillation level decreased from 12.5% to 4.1%, and drift deviation was reduced from 18.2 cm to 5.3 cm. Meanwhile, hovering accuracy and control responsiveness increased to 98.8% and 98.0%, respectively. These findings indicate that the optimization of PI tuning parameters combined with IMU sensor integration significantly enhanced quadcopter flight stability, reduced oscillation and drift, and improved control accuracy. Therefore, the proposed tuning method is considered effective for improving the performance and operational reliability of low-cost quadcopter flight controller systems.