Enhanced quadrotor motion analysis through extended kalman filtering

This paper aims to develop a stable quadrotor’s flight controller using the ESP32 microcontroller, enabling wireless guidance through a Graphical User Interface (GUI) on Raspberry Pi. In this context, an Extended Kalman Filter (EKF) with a nonlinear control model is employed to estimate the angular velocity and speed of the quadrotor. Simulationswere conducted using two nonlinear controllers (BackStepping Controller (BSC) and Sliding Mode Controller (SMC)) across various scenarios to prove the efficiency of the proposed method for trajectory tracking. The performance was analyzed using Root Mean Square Error (RMSE) and compared to previous works. It was noticed that in the both control scenarios, the estimated states followed the desired instructions, although a potential overshoot was noted in the case of SMC. Additionally, two control approaches were practically implemented. The first approach utilizes the classical Proportional Integral Derivative (PID) technique, while the second approach employs the modern Backstepping technique. The results demonstrate that both control approaches deliver satisfactory performance and responsiveness in stabilizing the quadrotor in real-world scenarios. However, it has been noticed that the Backstepping controller achieves higher performance, whereas, the PID controller’sperformance is constrained by tuning and model limitations.