@inproceedings{0ad9f0c703784b4495ff1d4862cbbadc,
title = "Fault-tolerant flight control for an air-breathing hypersonic vehicle using multivariable sliding mode and neural network",
abstract = "This paper presents a fault-tolerant control (FTC) with integration of neural network (NN) and multivariable sliding mode approaches for an air-breathing hypersonic vehicle (AHV), where both partial loss of effectiveness faults and bias faults in actuators are considered. A radial bias function NN (RBFNN) is derived using on-line updating law to approximate the lumped uncertainties, which consists of actuator faults and system uncertainties. A finite-time convergent multivariable sliding mode control (SMC) is developed against system uncertainties and actuator faults. Simulation results of a generic AHV are provided to demonstrate the effectiveness of the proposed FTC scheme.",
keywords = "Fault-tolerant control, air-breathing hypersonic vehicle, multivariable sliding mode, neural network",
author = "Peng Li and Xiang Yu and Jianjun Ma and Zhiqiang Zheng",
note = "Publisher Copyright: {\textcopyright} 2017 Technical Committee on Control Theory, CAA.; 36th Chinese Control Conference, CCC 2017 ; Conference date: 26-07-2017 Through 28-07-2017",
year = "2017",
month = sep,
day = "7",
doi = "10.23919/ChiCC.2017.8028500",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "7247--7252",
editor = "Tao Liu and Qianchuan Zhao",
booktitle = "Proceedings of the 36th Chinese Control Conference, CCC 2017",
address = "美国",
}