Abstract
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 language | English |
|---|---|
| Pages (from-to) | 623-628 |
| Number of pages | 6 |
| Journal | IFAC Proceedings Volumes (IFAC-PapersOnline) |
| Volume | 36 |
| Issue number | 20 |
| DOIs | |
| Publication status | Published - 2003 Jan 1 |
| Event | 5th IFAC Symposium on Power Plants and Power Systems Control 2003 - Seoul, Korea, Republic of Duration: 2003 Sep 15 → 2003 Sep 19 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
Fingerprint Dive into the research topics of 'Indirect adaptive neurocontrol scheme for a static compensator connected to a power system'. Together they form a unique fingerprint.
Cite this
Mohagheghi, S., Venayagamoorthy, G. K., Harley, R. G., Park, J. W., & Crow, M. L. (2003). Indirect adaptive neurocontrol scheme for a static compensator connected to a power system. IFAC Proceedings Volumes (IFAC-PapersOnline), 36(20), 623-628. https://doi.org/10.1016/S14746670(17)34539-1