Sliding Mode Control for Hypersonic Vehicle Based on Extreme Learning Machine Neural Network Disturbance Observer

doi:10.1109/ACCESS.2022.3185256

	Sliding Mode Control for Hypersonic Vehicle Based on Extreme Learning Machine Neural Network Disturbance Observer
	Gao, Haiyan 2; Tang, Weiqiang 1; Fu, Rong 2
刊名	IEEE Access
	2022
卷号	10 页码:69333-69345
关键词	Altitude control Control theory Hypersonic aerodynamics Hypersonic vehicles Knowledge acquisition Learning systems Navigation Network layers Sliding mode control Disturbance observer Extreme learning machine Learning machines Network disturbances Neural network disturbance observer Neural-networks Offset-free tracking Sliding-mode control Uncertainty Vehicle's dynamics
ISSN号	2169-3536
DOI	10.1109/ACCESS.2022.3185256
英文摘要	The novel extreme learning machine (ELM) neural network disturbance observer (NNDO) -based sliding mode control (SMC) strategy is proposed for the precise tracking control of a hypersonic vehicle (HV) under various disturbance situations. By converting nonlinear dynamics into state-dependent linear model, the control law design process is simplified, and the sliding mode control law based on the power function reaching rate is designed to suppress the chattering effect. Considering the disturbances, the ELM-NNDO is designed based on the single-hidden layer feedforward network (SLFN). Different from conventional ELM using least square optimization approach, the output weight here is updated based on the Lyapunov synthesis approach. In addition, the influences of the disturbances on the velocity and altitude are attenuated by the direct feedback compensation (DFC), and the offset-free tracking control is realized for the output reference signal. Comparison of simulation results verify the superior control performance of the proposed method. © 2013 IEEE.
WOS研究方向	Computer Science ; Engineering ; Telecommunications
语种	英语
出版者	Institute of Electrical and Electronics Engineers Inc.
WOS记录号	WOS:000838380700001
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/159385]
专题	电气工程与信息工程学院
作者单位	1.Lanzhou University of Technology, College of Electrical and Information Engineering, Lanzhou; 730050, China 2.Xiamen University of Technology, School of Electrical Engineering and Automation, Xiamen; 361024, China;
推荐引用方式 GB/T 7714	Gao, Haiyan,Tang, Weiqiang,Fu, Rong. Sliding Mode Control for Hypersonic Vehicle Based on Extreme Learning Machine Neural Network Disturbance Observer[J]. IEEE Access,2022,10:69333-69345.
APA	Gao, Haiyan,Tang, Weiqiang,&Fu, Rong.(2022).Sliding Mode Control for Hypersonic Vehicle Based on Extreme Learning Machine Neural Network Disturbance Observer.IEEE Access,10,69333-69345.
MLA	Gao, Haiyan,et al."Sliding Mode Control for Hypersonic Vehicle Based on Extreme Learning Machine Neural Network Disturbance Observer".IEEE Access 10(2022):69333-69345.