Scholars' Mine
Missouri S&T
Research Repository
Curtis Laws Wilson Library
400 W. 14th Street
Rolla, MO 65409-0060
scholarsmine@mst.edu
| Title: | An adaptive neural network identifier for effective control of a static compensator connected to a power system | |
| Author (s): | Mohagheghi, S. Park, Jung-Wook Harley, R.G. Venayagamoorthy, Ganesh K. Crow, Mariesa L. | |
| Department/Lab Affiliations: | Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory | |
| Keywords: | adaptive neural network identifier adaptive neurocontroller continually online trained artificial neural networks identification neurocontrollers power electronic based shunt connected flexible AC transmission system devices power system power system control static VAr compensators static compensator | |
| Issue Date: | 2003 | |
| Publisher: | Institute of Electrical and Electronics Engineers | |
| Citation: | Mohagheghi, S.; Jung-Wook Park; Harley, R.G.; Venayagamoorthy, G.K.; Crow, M.L., "An adaptive neural network identifier for effective control of a static compensator connected to a power system," Proceedings of the International Joint Conference on Neural Networks, vol.4, pp. 2964- 2969, 20-24 July 2003 | |
| Abstract: | A novel method for nonlinear identification of a static compensator connected to a power system using continually online trained (COT) artificial neural networks (ANNs) is presented in this paper. The identifier is successfully trained online to track the dynamics of the power network without any need for offline data and can be used in designing an adaptive neurocontroller for a static compensator connected to such system. | |
| Type: | Article - Conference proceedings text | |
| Copyright Notice: | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. FULL COPYRIGHT INFORMATION: | |
| Publisher URL: | ||
| Link to this page: | ||
| Full Text: |
|
| title | An adaptive neural network identifier for effective control of a static compensator connected to a power system | |
| contributor.author | Mohagheghi, S. | |
| contributor.author | Park, Jung-Wook | |
| contributor.author | Harley, R.G. | |
| contributor.author | Venayagamoorthy, Ganesh K. | |
| contributor.author | Crow, Mariesa L. | |
| contributor.deptlab | Electrical and Computer Engineering | |
| contributor.deptlab | Real-Time Power and Intelligent Systems Laboratory | |
| subject | adaptive neural network identifier | |
| subject | adaptive neurocontroller | |
| subject | continually online trained artificial neural networks | |
| subject | identification | |
| subject | neurocontrollers | |
| subject | power electronic based shunt connected flexible AC transmission system devices | |
| subject | power system | |
| subject | power system control | |
| subject | static VAr compensators | |
| subject | static compensator | |
| date.issued | 2003 | |
| date.submitted | 2007 | |
| publisher | Institute of Electrical and Electronics Engineers | |
| identifier.citation | Mohagheghi, S.; Jung-Wook Park; Harley, R.G.; Venayagamoorthy, G.K.; Crow, M.L., "An adaptive neural network identifier for effective control of a static compensator connected to a power system," Proceedings of the International Joint Conference on Neural Networks, vol.4, pp. 2964- 2969, 20-24 July 2003 | |
| identifier.issn | 1098-7576 | |
| identifier.pub.URI | ||
| description.abstract | A novel method for nonlinear identification of a static compensator connected to a power system using continually online trained (COT) artificial neural networks (ANNs) is presented in this paper. The identifier is successfully trained online to track the dynamics of the power network without any need for offline data and can be used in designing an adaptive neurocontroller for a static compensator connected to such system. | |
| type | Article - Conference proceedings | |
| type.DCMIType | text | |
| type.status | Final version | |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | |
| rights.URI | ||
| date.accessioned | 2007-04-05T14:17:22Z | |
| date.available | 2007-04-05T14:17:22Z | |
| identifier.persist.URI | ||
| Full Text |
|