Indirect adaptive neurocontrol scheme for a static compensator connected to a power system

Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley, Jung Wook Park, Mariesa L. Crow

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)


An indirect adaptive neurocontrol scheme for a Static Compensator connected to a power system using two Artificial Neural Networks (ANNs) is presented in this paper. The ANNs are trained online and there is no need for offline data. The neurocontroller has a better performance in adaptively controlling the Static Compensator and damping the system transients, compared to conventional controllers. Preliminary results are provided to show the performance of the neurocontroller for large disturbances.

Original languageEnglish
Pages (from-to)623-628
Number of pages6
JournalIFAC Proceedings Volumes (IFAC-PapersOnline)
Issue number20
Publication statusPublished - 2003
Event5th IFAC Symposium on Power Plants and Power Systems Control 2003 - Seoul, Korea, Republic of
Duration: 2003 Sep 152003 Sep 19

Bibliographical note

Funding Information:
Financial support by the National Science Foundation (NSF), USA under Grant No. ECS-023 1632 and from the Duke Power Company, Charlotte, North Carolina, USA, for this research is gratefully acknowledged.

Publisher Copyright:
© 2003 IFAC.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering


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