Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1640
Title: Adaptive B-spline network control for three-phase PWM AC-DC voltage source converter
Authors: Cheng, KWE 
Wang, HY
Sutanto, D
Keywords: Adaptive control systems
Computer simulation
Electric currents
Electric distortion
Electric power factor
Electric waveforms
Learning algorithms
Lyapunov methods
Mathematical models
Online systems
Power converters
Pulse width modulation
Issue Date: 1999
Publisher: IEEE
Source: PEDS'99 : proceedings of the IEEE 1999 International Conference on Power Electronics and Drive Systems : 27-29 July 1999, Hong Kong, p. 467-472 How to cite?
Abstract: A neural network control method - adaptive B-spline neural network for three-phase AC-DC voltage source converters that realizes a sinusoidal ac input current and unity power factor is discussed in this paper. Comparing to the other PWM techniques, the main advantage of the neural network is that it has excellent merit for nonlinear control and is adaptive enough to fit the environment change. Since the training for the network is on-line in this paper, it is more robust to external disturbances. B-spline neural network is used because it is characterized by a local weight updating scheme with the advantages of fast convergence speed and low computation complexity. This is fairly important for real-time control application. The stability of the network control strategy can be shown using Lyapunov law. Simulation results are presented to illustrate the effectiveness of the proposed control strategy.
URI: http://hdl.handle.net/10397/1640
ISBN: 0-7803-5769-8
Rights: © 1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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