Indirect adaptive control for synchronous generator: Comparison of MLP/RBF neural networks approach with Lyapunov stability analysis

Jung Wook Park, Ronald G. Harley, Ganesh K. Venayagamoorthy

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

This paper compares two indirect adaptive neurocontrollers, namely a multilayer perceptron neurocontroller (MLPNC) and a radial basis function neurocontroller (RBFNC) to control a synchronous generator. The different damping and transient performances of two neurocontrollers are compared with those of conventional linear controllers, and analyzed based on the Lyapunov direct method.

Original languageEnglish
Pages (from-to)460-464
Number of pages5
JournalIEEE Transactions on Neural Networks
Volume15
Issue number2
DOIs
Publication statusPublished - 2004 Mar

Bibliographical note

Funding Information:
Manuscript received August 28, 2002; revised June 25, 2003. This work was supported in part by the National Science Foundation (NSF), under Grant ECS-0080764 and in part by the Duke Power Company, Charlotte, NC.

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

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