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Adaptive Neural Sliding Mode Control of Active Power Filter
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-05-09
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
A radial basis function (RBF) neural network adaptive sliding mode control system is developed for the current compensation control of three-phase active power filter (APF).
The advantages of the adaptive control, neural network control, and sliding mode control are combined together to achieve the control task; that is, the harmonic current of nonlinear load can be eliminated and the quality of power system can be well improved.
Sliding surface coordinate function and sliding mode controller are used as input and output of the RBF neural network, respectively.
The neural network control parameters are online adjusted through gradient method and Lyapunov theory.
Simulation results demonstrate that the adaptive RBF sliding mode control can compensate harmonic current effectively and has strong robustness to disturbance signals.
American Psychological Association (APA)
Fei, Juntao& Wang, Zhe. 2013. Adaptive Neural Sliding Mode Control of Active Power Filter. Journal of Applied Mathematics،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-464275
Modern Language Association (MLA)
Fei, Juntao& Wang, Zhe. Adaptive Neural Sliding Mode Control of Active Power Filter. Journal of Applied Mathematics No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-464275
American Medical Association (AMA)
Fei, Juntao& Wang, Zhe. Adaptive Neural Sliding Mode Control of Active Power Filter. Journal of Applied Mathematics. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-464275
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-464275