Abstract
In this work, the main objective is to study the Optimal Kalman Filtering (OKF) method for estimating the state vector of a small quadrotor UAV through incorporating the internal disturbances including the white Gaussian process and measurement noises. Firstly, the kinematic and dynamic model of the quadrotor is transformed into a discrete-time system via the linear extrapolation method. Secondly, for the sake of performing the high accuracy position and attitude tracking control of the quadrotor, the discrete-time flight controller is designed using second order discrete-time sliding mode technique. In addition, the estimation of the quadrotor aircraft's state vector is carried out with the use of OKF. The performance of the combination between the flight controller and the OKF is evaluated through simulation tests. Extensive simulation results show that the combined strategy has a good performance in terms of variance and state estimation.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.