A B-spline network based neural controller for power electronic applications

  • Authors:

  • Heng Deng;Dipti Srinivasan;Ramesh Oruganti

  • Affiliations:

  • Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, National University of Singapore, 117576 Singapore, Republic of Singapore;Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, National University of Singapore, 117576 Singapore, Republic of Singapore;Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, National University of Singapore, 117576 Singapore, Republic of Singapore

  • Venue:
  • Neurocomputing
  • Year:
  • 2010

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Abstract

Conventional multi-layer feedforward ANN controllers with back-propagation training are too complex to be implemented in fast-dynamic power electric systems. This paper proposes a controller for power electric systems based on a type of on-line trained neural network called the B-spline network (BSN). Due to its linear nature and local weight updating, the BSN controller is more suitable for real-time implementation than conventional multi-layer feedforward neural controllers. Based on a frequency domain stability analysis, a design methodology for determining the two main parameters of the BSN is presented. The design procedure of the proposed BSN controller is straightforward and simple. Experimental results of UPS inverters with the proposed controller under various conditions show that the proposed controller can achieve excellent performance.