Neural network based control for synchronous generators

E. Swidenbank, Seán McLoone, Damian Flynn, George Irwin, Michael Brown, Brian Hogg

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)


In this paper, a Radial Basis Function neural network based AVR is proposed. A control strategy which generates local linear models from a global neural model on-line is used to derive controller feedback gains based on the Generalised Minimum Variance technique. Testing is carried out on a micromachine system which enables evaluation of practical implementation of the scheme. Constraints imposed by gathering training data, computational load, and memory requirements for the training algorithm are addressed.
Original languageEnglish
Pages (from-to)1673-1678
Number of pages6
JournalIEEE Transactions on Energy Conversion
Issue number4
Publication statusPublished - 1999

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Fuel Technology
  • Electrical and Electronic Engineering


Dive into the research topics of 'Neural network based control for synchronous generators'. Together they form a unique fingerprint.

Cite this