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https://doi.org/10.1080/00051144.2018.1486797

Robust adaptive neural network control for switched reluctance motor drives

Cunhe Li ; Shool of Information Science and Technology, Dalian Maritime University, Dalian, People’s Republic of China
Guofeng Wang ; Shool of Information Science and Technology, Dalian Maritime University, Dalian, People’s Republic of China
Yan Li ; Shool of Information Science and Technology, Dalian Maritime University, Dalian, People’s Republic of China
Aide Xu ; Shool of Information Science and Technology, Dalian Maritime University, Dalian, People’s Republic of China

Puni tekst: engleski, pdf (3 MB) str. 24-34 preuzimanja: 94* citiraj
APA 6th Edition
Li, C., Wang, G., Li, Y. i Xu, A. (2018). Robust adaptive neural network control for switched reluctance motor drives. Automatika, 59 (1), 24-34. https://doi.org/10.1080/00051144.2018.1486797
MLA 8th Edition
Li, Cunhe, et al. "Robust adaptive neural network control for switched reluctance motor drives." Automatika, vol. 59, br. 1, 2018, str. 24-34. https://doi.org/10.1080/00051144.2018.1486797. Citirano 09.07.2020.
Chicago 17th Edition
Li, Cunhe, Guofeng Wang, Yan Li i Aide Xu. "Robust adaptive neural network control for switched reluctance motor drives." Automatika 59, br. 1 (2018): 24-34. https://doi.org/10.1080/00051144.2018.1486797
Harvard
Li, C., et al. (2018). 'Robust adaptive neural network control for switched reluctance motor drives', Automatika, 59(1), str. 24-34. https://doi.org/10.1080/00051144.2018.1486797
Vancouver
Li C, Wang G, Li Y, Xu A. Robust adaptive neural network control for switched reluctance motor drives. Automatika [Internet]. 2018 [pristupljeno 09.07.2020.];59(1):24-34. https://doi.org/10.1080/00051144.2018.1486797
IEEE
C. Li, G. Wang, Y. Li i A. Xu, "Robust adaptive neural network control for switched reluctance motor drives", Automatika, vol.59, br. 1, str. 24-34, 2018. [Online]. https://doi.org/10.1080/00051144.2018.1486797

Sažetak
This article presents a robust adaptive neural network controller for switched reluctance motor (SRM) speed control with both parameter variations and external load disturbances. The radial basis function neural network with the technology of minimal learning parameters is employed to approximate an ideal control law which includes the parameter variations and external disturbances. Furthermore, a proportional control term is introduced to improve the transient
performance and chattering phenomena of the SRM drive system. The asymptotic stability of the proposed controller is guaranteed through rigorous Lyapunov analysis. A main advantage of the proposed control scheme is that it contains only one adaptive parameter that needs to be
updated on-line. This advantage result in a much simpler adaptive control algorithm, which is convenient to implement in switched reluctance drives. Finally, the simulations and experiments are carried out to demonstrate the effectiveness of the proposed control scheme.

Ključne riječi
Switched reluctance motor; speed control; adaptive neural network control; parameter variations; external load disturbances

Hrčak ID: 225174

URI
https://hrcak.srce.hr/225174

Posjeta: 152 *