An RBFNN-Based Direct Inverse Controller for PMSM with Disturbances
Joint Authors
Li, Shengquan
Li, Juan
Shi, Yanqiu
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-06-13
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Considering the system uncertainties, such as parameter changes, modeling error, and external uncertainties, a radial basis function neural network (RBFNN) controller using the direct inverse method with the satisfactory stability for improving universal function approximation ability, convergence, and disturbance attenuation capability is advanced in this paper.
The weight adaptation rule of the RBFNN is obtained online by Lyapunov stability analysis method to guarantee the identification and tracking performances.
The simulation example for the position tracking control of PMSM is studied to illustrate the effectiveness and the applicability of the proposed RBFNN-based direct inverse control method.
American Psychological Association (APA)
Li, Shengquan& Li, Juan& Shi, Yanqiu. 2018. An RBFNN-Based Direct Inverse Controller for PMSM with Disturbances. Complexity،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1133934
Modern Language Association (MLA)
Li, Shengquan…[et al.]. An RBFNN-Based Direct Inverse Controller for PMSM with Disturbances. Complexity No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1133934
American Medical Association (AMA)
Li, Shengquan& Li, Juan& Shi, Yanqiu. An RBFNN-Based Direct Inverse Controller for PMSM with Disturbances. Complexity. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1133934
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1133934