TY - JOUR
T1 - An adaptive trajectory tracking control of four rotor hover vehicle using extended normalized radial basis function network
AU - ul Amin, Rooh
AU - Aijun, Li
AU - Khan, Muhammad Umer
AU - Shamshirband, Shahaboddin
AU - Kamsin, Amirrudin
N1 - Publisher Copyright:
© 2016 Elsevier Ltd
PY - 2017/1/15
Y1 - 2017/1/15
N2 - In this paper, an adaptive trajectory tracking controller based on extended normalized radial basis function network (ENRBFN) is proposed for 3-degree-of-freedom four rotor hover vehicle subjected to external disturbance i.e. wind turbulence. Mathematical model of four rotor hover system is developed using equations of motions and a new computational intelligence based technique ENRBFN is introduced to approximate the unmodeled dynamics of the hover vehicle. The adaptive controller based on the Lyapunov stability approach is designed to achieve tracking of the desired attitude angles of four rotor hover vehicle in the presence of wind turbulence. The adaptive weight update based on the Levenberg-Marquardt algorithm is used to avoid weight drift in case the system is exposed to external disturbances. The closed-loop system stability is also analyzed using Lyapunov stability theory. Simulations and experimental results are included to validate the effectiveness of the proposed control scheme.
AB - In this paper, an adaptive trajectory tracking controller based on extended normalized radial basis function network (ENRBFN) is proposed for 3-degree-of-freedom four rotor hover vehicle subjected to external disturbance i.e. wind turbulence. Mathematical model of four rotor hover system is developed using equations of motions and a new computational intelligence based technique ENRBFN is introduced to approximate the unmodeled dynamics of the hover vehicle. The adaptive controller based on the Lyapunov stability approach is designed to achieve tracking of the desired attitude angles of four rotor hover vehicle in the presence of wind turbulence. The adaptive weight update based on the Levenberg-Marquardt algorithm is used to avoid weight drift in case the system is exposed to external disturbances. The closed-loop system stability is also analyzed using Lyapunov stability theory. Simulations and experimental results are included to validate the effectiveness of the proposed control scheme.
KW - Adaptive neural network control
KW - Extended normalized radial basis function
KW - Four rotor hover vehicle
KW - Unmodeled dynamics approximation
UR - http://www.scopus.com/inward/record.url?scp=84995685085&partnerID=8YFLogxK
U2 - 10.1016/j.ymssp.2016.05.043
DO - 10.1016/j.ymssp.2016.05.043
M3 - 文章
AN - SCOPUS:84995685085
SN - 0888-3270
VL - 83
SP - 53
EP - 74
JO - Mechanical Systems and Signal Processing
JF - Mechanical Systems and Signal Processing
ER -