Adaptive recurrent-functional-link-network control for hypersonic vehicles with atmospheric disturbances

被引：0
作者：
YanLi Du
QingXian Wu
ChangSheng Jiang
YaLi Xue
机构：
[1] Nanjing University of Aeronautics and Astronautics,College of Astronautics
[2] Nanjing University of Aeronautics and Astronautics,College of Automation Engineering
来源：
Science China Information Sciences | 2011年 / 54卷
关键词：
near-space hypersonic vehicle; atmospheric disturbances; nonlinear predictive control; adaptive control; B-spline recurrent functional link network;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The controller design for a near-space hypersonic vehicle (NHV) is challenging due to its plant uncertainties and sensitivity to atmospheric disturbances such as gusts and turbulence. This paper first derives 12 states equations of NHVs subjected to variable wind field, and presents a novel recurrent neural network (RNN) control method for restraining atmospheric disturbances. The method devises a new B-spline recurrent functional link network (BRFLN) and combines it with the nonlinear generalized predictive control (NGPC) algorithm. Moreover, the proportional-derivative (PD) correction BRFLN is proposed to approximate atmospheric disturbances in flight. The weights of BRFLN are online tuned by the adaptive law based on Lyapunov stability theorem. Finally, simulation results show a satisfactory performance for the attitude tracking of the NHV in the mesosphere, and also illustrate the controller’s robustness to wind turbulence.
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页码：482 / 497
页数：15
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