Adaptive B-spline network control for three-phase PWM AC-DC voltage source converter

Ka Wai Eric Cheng, H. Y. Wang, D. Sutanto

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

8 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Power Electronics and Drive Systems
PublisherIEEE
Pages467-472
Number of pages6
Publication statusPublished - 1 Dec 1999
EventProceedings of the 1999 3rd IEEE International Conference on Power Electronics and Drive Systems (PEDS'99) - Kowloon, Hong Kong
Duration: 27 Jul 199929 Jul 1999

Conference

ConferenceProceedings of the 1999 3rd IEEE International Conference on Power Electronics and Drive Systems (PEDS'99)
Country/TerritoryHong Kong
CityKowloon
Period27/07/9929/07/99

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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