In this section
@inproceedings{Arif:2009:10.1109/IJCNN.2009.5179071,
author = {Arif, J and Chaudhuri, NR and Ray, S and Chaudhuri, B},
doi = {10.1109/IJCNN.2009.5179071},
pages = {199--206},
publisher = {IEEE},
title = {Online Levenberg-Marquardt algorithm for neural network based estimation and control of power systems},
url = {http://dx.doi.org/10.1109/IJCNN.2009.5179071},
year = {2009}
}
TY - CPAPER
AB - Levenberg-Marquardt (LM) algorithm, a powerfuloff-line batch training method for neural networks, is adaptedhere for online estimation of power system dynamic behavior.A special form of neural network compatible with the feedbacklinearization framework is used to enable non-linear self-tuningcontrol. Use of LM is shown to yield better closed-loop performancecompared to conventional recursive least square (RLS) approach.For successive disturbance use of LM in conjunction withnon-linear neural network structure yields faster convergencecompared to RLS. A case study on a test system demonstratesthe effectiveness of the online LM method for both linear andnonlinear estimation over RLS estimation (linear).
AU - Arif,J
AU - Chaudhuri,NR
AU - Ray,S
AU - Chaudhuri,B
DO - 10.1109/IJCNN.2009.5179071
EP - 206
PB - IEEE
PY - 2009///
SN - 1098-7576
SP - 199
TI - Online Levenberg-Marquardt algorithm for neural network based estimation and control of power systems
UR - http://dx.doi.org/10.1109/IJCNN.2009.5179071
UR - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5179071&isnumber=5178557
UR - http://hdl.handle.net/10044/1/26613
ER -