A Neural Network Adaptive Fault-Tolerant Control Method for Launch Vehicles with the Limited Faults

被引：3
|
作者：
Zhu H. [1 ]
Wu Y. [2 ]
Rong Y. [1 ]
Qin X. [1 ]
Chen Y. [1 ]
机构：
[1] Beijing Institute of Astronautical Systems Engineering, Beijing
[2] China Aerospace Science and Technology Corporation, Beijing
来源：
Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University | 2020年 / 38卷 / 03期
关键词：
Active fault-tolerant control; Adaptive control; Limited faults; Radial basis function neural network;
D O I：
10.1051/jnwpu/20203830668
中图分类号：
学科分类号：
摘要：
To tolerate the limited faults such as thrust decline or actuator jamming of launch vehicles, an adaptive fault-tolerant control method based on radial basis function neural network (RBFNN) is proposed in this paper. The method is based on a limited faults dynamics model, and the baseline controller is designed based on the pole placement, using RBFNN to online identify and compensate the fault parameters and uncertain disturbances in the model. Then an adaptive fault-tolerant control law is designed based on Lyapunov theory. The simulation results show that the proposed adaptive control method can effectively ensure the attitude stability as well as control accuracy under the limited faults of launch vehicles, compared with the traditional PD control method. © 2020 Journal of Northwestern Polytechnical University.
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页码：668 / 676
页数：8
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