@article{MAKHILLIJSSCEA201710628812,
    title = {Tracking Control of Quadrotor using NonLinear Quadratic Tracking With Extended Kalman
Filter},
    journal = {International Journal of System Signal Control and Engineering Application},
    volume = {10},
    number = {6},
    pages = {147-152},
    year = {2017},
    issn = {1997-5422},
    doi = {ijssceapp.2017.147.152},
    url = {https://makhillpublications.co/view-article.php?issn=1997-5422&doi=ijssceapp.2017.147.152},
    author = {Mohammad,Trihastuti and},
    keywords = {Quadrotor,nonlinear quadratic tracking,extended Kalman filter,UAV,NLQT},
    abstract = {Quadrotor is one of the Unmanned Aerial
Vehicle (UAV) which is a MIMO system and has a
non-linear dynamics. The nonlinearity properties of
rotational motion and translational motion of quadrotor
are very high and the control inputs interact each other.
The interaction between the control inputs lead to system
instability. This characteristic causes difficulties in
tracking quadrotor automatically. Quadratic Nonlinear
Tracking (NLQT) is used to overcome the problem of
tracking in quadrotor with maintaining the linear nature of
the matrix B. NQLT is developed from Linear Quadratic
control method Tracking (LQT). The Extended Kalman
Filter (EKF) is used as a state estimator to overcome the
noise measurement. Based on the test results before the
addition of the EKF, the proposed method provides the
excellent performance of quadrotor in tracking.
Quantitatively, the quadrotor can track the given reference
signal with the position errors of quadrotor are 0.009 on
the x-axis and 0.0099 m on the y-axis 0.0095 m for the
measurement noise with zero mean and variance of 0.009.
The addition of the EKF on the control system and by
using the same noise properties, the position error
along the x-axis and y-axis, respectively are 0.0062 and
0.0062 m.}
    }