Nonlinear estimation of quadcopter states using unscented Kalman filter

Ahmed Abdulmahdi Abdulkareem Alawsi, Basil H Jasim, Safanah Mudheher Raafat

Abstract


In recent years, using Unmanned Arial Vehicles (UAV) like quadcopter in civilian and military fields are increased dramatically. Performance and robustness are the most important specifications required for most applications. Different sensors are usually used for a quadcopter to provide the necessary measured states (attitude and position) for control. The white noise generated by physical sensors is one of the important issues that affect the quality of states measurements. The available solutions are still have limited performance for a wide range of nonlinearity. In this paper, Unscented Kalman Filter (UKF) is proposed as a robust estimator that has the ability to work efficiently with high nonlinear systems. Modified PID (PI-D) controller which has better properties than traditional PID controller is used with proposed filter in order to get better performance of quadcopter. The obtained results are compared with that of Extended Kalman Filter (EKF) and proved to be more reliable. Moreover, the results show that the proposed filter largely decreases the error generated by noise and improves the performance of quadcopter better than the EKF.

Keywords


Quadcopter PID controller Autonomous flight Delivery by quadcopter Sensor noise of quadcopter, UKF EKF

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DOI: http://dx.doi.org/10.21533/pen.v7i4.878

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ISSN: 2303-4521

Digital Object Identifier DOI: 10.21533/pen

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License