TY - JOUR
T1 - Adaptive decoupling control of hypersonic vehicle using fuzzy-neural network observer
AU - Bai, Chen
AU - Chen, Jian
AU - Ren, Zhang
AU - Li, Qingdong
AU - Xiong, Zihao
N1 - Publisher Copyright:
© Institution of Mechanical Engineers 2016.
PY - 2016/6
Y1 - 2016/6
N2 - An adaptive decoupling control approach using fuzzy-neural network (FNN) observer for a class of MIMO nonlinear systems with parameter uncertainties is presented in this article. First, a decoupling controller is constructed based on the decentralized control theory. Furthermore, the system coupling terms and uncertainties are estimated by the FNN observer and added into the control law for compensation. The FNN approximate-matrix update law and the control law guarantee that the tracking errors of the system states, the observer states and the approximate matrix are all uniformly ultimately bounded within a region that can be kept arbitrarily small. Secondly, a model for the hypersonic vehicle is given and an attitude controller is designed using the decoupling control approach. Finally, simulations are carried out on the hypersonic vehicle to demonstrate the effectiveness of the proposed method.
AB - An adaptive decoupling control approach using fuzzy-neural network (FNN) observer for a class of MIMO nonlinear systems with parameter uncertainties is presented in this article. First, a decoupling controller is constructed based on the decentralized control theory. Furthermore, the system coupling terms and uncertainties are estimated by the FNN observer and added into the control law for compensation. The FNN approximate-matrix update law and the control law guarantee that the tracking errors of the system states, the observer states and the approximate matrix are all uniformly ultimately bounded within a region that can be kept arbitrarily small. Secondly, a model for the hypersonic vehicle is given and an attitude controller is designed using the decoupling control approach. Finally, simulations are carried out on the hypersonic vehicle to demonstrate the effectiveness of the proposed method.
KW - Adaptive decoupling control
KW - Fuzzy-neural network observer
KW - Hypersonic vehicle
KW - MIMO nonlinear systems
KW - Parameter uncertainties
UR - https://www.scopus.com/pages/publications/84971272994
U2 - 10.1177/0954410015606165
DO - 10.1177/0954410015606165
M3 - 文章
AN - SCOPUS:84971272994
SN - 0954-4100
VL - 230
SP - 1216
EP - 1223
JO - Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
JF - Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
IS - 7
ER -