1
Electerical Engineering, Indian Institute of Technology
2
Department of Electrical and Computer Engineering, University of Calgary
3
Engineering, Dayalbagh Educational Institute
Abstract
An artificial neural network can be used as an intelligent controller to control non-linear, dynamic system through learning. It can easily accommodate non-linearities and time dependencies. Most common multi-layer feed-forward neural networks have the drawbacks of large number of neurons and hidden layers required to deal with complex problems and require large training time. To overcome these drawbacks, a generalized neuron based non-linear controller has been developed and illustrated as a power system stabilizer. Studies on a five machine power system show that the proposed controller can significantly improve the dynamic performance and provide good damping of the power system over a wide operating range.
Kalra, P. K., Malik, O. P., & Chaturvedi, D. K. (2004). Studies with a Generalized Neuron Based PSS on a Multi-Machine Power System. International Journal of Engineering, 17(2), 131-140.
MLA
P. K. Kalra; O. P. Malik; D. K. Chaturvedi. "Studies with a Generalized Neuron Based PSS on a Multi-Machine Power System". International Journal of Engineering, 17, 2, 2004, 131-140.
HARVARD
Kalra, P. K., Malik, O. P., Chaturvedi, D. K. (2004). 'Studies with a Generalized Neuron Based PSS on a Multi-Machine Power System', International Journal of Engineering, 17(2), pp. 131-140.
VANCOUVER
Kalra, P. K., Malik, O. P., Chaturvedi, D. K. Studies with a Generalized Neuron Based PSS on a Multi-Machine Power System. International Journal of Engineering, 2004; 17(2): 131-140.