@inproceedings{94ca6ef657294cf38a34c5c8f551637d,
title = "Design of Fractional-order Global Sliding Mode Controller for Thermal-Structure Test based on Neural Network",
abstract = "In this paper, a fractional-order global sliding mode control (FOGSMC) scheme based on a neural network with approximation property (NNO) is mainly focused on study the thermal-structural test (TST) system. Since the nonlinear dynamic system of the thermal-structure test with quartz lamp is susceptible to external interference and parameter variation, a novel FOGSMC system is designed based on improved fractional order global terminal sliding surface to acquire the desired trajectory, and real time estimation of system disturbance using neural network observer with Gaussian Function, meanwhile, the fractional-order global terminal sliding mode surface based on fractional-order function can effectively weaken the chattering phenomenon of the integer order, simulation studies show the effectiveness of the proposed method.",
keywords = "hypersonic aircraft, nonlinear extended state observer, sliding mode control",
author = "Yue Wang and Guangming Zhang and Xiaodong Lv and Gang Wang and Zhiqing Bai",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE.; 2022 International Conference on Mechatronics Engineering and Artificial Intelligence, MEAI 2022 ; Conference date: 11-11-2022 Through 13-11-2022",
year = "2023",
doi = "10.1117/12.2671934",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Chuanjun Zhao",
booktitle = "2022 International Conference on Mechatronics Engineering and Artificial Intelligence, MEAI 2022",
address = "美国",
}