Open AccessPostural Stabilization of Quadrotor using Extended Kalman Filter and Integral Sliding Mode Control
Author(s) -
Hyukwoo Lee,
Kyunghyun Lee,
Kwanho You
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/630/1/012002
Subject(s) - control theory (sociology) , integral sliding mode , extended kalman filter , kalman filter , noise (video) , controller (irrigation) , disturbance (geology) , nonlinear system , computer science , sliding mode control , control engineering , filter (signal processing) , engineering , control (management) , artificial intelligence , physics , computer vision , paleontology , quantum mechanics , agronomy , image (mathematics) , biology
In this paper, we consider the stabilization and the estimate of quadrotor’s posture. Nowadays, as the interest in unmanned aerial vehicle (UAV) has increased, various application fields using UAV have appeared. The quadrotor is the most common type of UAV and many approaches to control the system have been studied. In real control environment, the system of quadrotor is affected by disturbance and measurement noise. Minimizing the effects of disturbance or measurement noise is important part. We propose the extended kalman filter (EKF) to reduce effectively the measurement noise of the nonlinear drones system and the integral sliding mode control (ISMC), a robust controller for the model uncertainty and disturbance. We show the proposed control performance through some simulations.