期刊
NEUROCOMPUTING
卷 363, 期 -, 页码 273-280出版社
ELSEVIER
DOI: 10.1016/j.neucom.2019.06.063
关键词
Adaptive control; Nonstrict feedback nonlinear systems; Backstepping; Fixed-time control; Neural networks
资金
- Funds of National Science of China [61603166, 61773188]
- Doctoral Research Initiation of Foundation of Liaoning Province [20180540047]
- Nursery Seedling Project for Young Scientiflc and Technological Talents of Liaoning Province [JQL201915402]
This paper addresses the fixed-time adaptive neural control of nonstrict feedback nonlinear system. With the help of neural networks and the backstepping technical, a fixed-time adaptive neural control scheme is presented. To guarantee closed-loop stability, a new semiglobal practical fixed-time stability (SPFTS) criterion is set up. Based on the established SPFTS criterion, we can show that both the tracking performance and the closed-loop stability can be preserved in a fixed time via the presented approach. Compared with the existing finite-time control, the convergence time of the propose fixed-time control scheme does not rely on the initial states. Finally, the proposed technique is demonstrated with simulation results. (C) 2019 Elsevier B.V. All rights reserved.
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