Adaptive dynamic surface control using neural networks for hypersonic flight vehicle with input nonlinearities

2020 ◽  
Vol 41 (6) ◽  
pp. 1904-1927 ◽  
Author(s):  
Lilin Zhou ◽  
Lei Liu ◽  
Zhongtao Cheng ◽  
Bo Wang ◽  
Huijin Fan
Keyword(s):  
Neural Networks ◽  
Dynamic Surface Control ◽  
Flight Vehicle ◽  
Dynamic Surface ◽  
Hypersonic Flight Vehicle ◽  
Adaptive Dynamic ◽  
Hypersonic Flight ◽  
Surface Control ◽  
Adaptive Dynamic Surface Control

scholarly journals LESO Based Dynamic Surface Control for Hypersonic Flight Vehicle

2018 ◽  
Vol 36 (1) ◽  
pp. 13-19
Author(s):  
Ke Zhang ◽  
Wenjun Yang ◽  
Minghuan Zhang ◽  
Pei Wang
Keyword(s):  
Dynamic Surface Control ◽  
Lyapunov Theory ◽  
Parametric Uncertainties ◽  
Flight Vehicle ◽  
External Disturbances ◽  
Dynamic Surface ◽  
Pass Filter ◽  
Hypersonic Flight Vehicle ◽  
Hypersonic Flight ◽  
Surface Control

In the presence of model parametric uncertainties and external disturbances, a LESO-based dynamic surface control approach is designed for the longitudinal model of Hypersonic Flight Vehicle (HFV). Via Nonlinear Dynamic Inversion (NDI) technique, the decoupling of altitude and velocity is realized. Combining with conventional back-stepping technique, a low pass filter (LPF) is introduced to attain the derivation of virtual control laws, which avoids the problem of "differentiation explosion". A linear extended state observer (LESO) is designed for the precise estimation and compensation of "lumped disturbance" containing parametric uncertainties and external disturbances, which tremendously improves the ability of disturbance rejection of the system. The stability of the proposed approach is analyzed by means of Lyapunov theory. The simulation results demonstrate that the proposed methodology has good command tracking performance, and the approach is robust in the presence of lumped disturbances.

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