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A Generalized Neuron Based Pss In A Multi-Machine Power System, D. K. Chaturvedi, O. P. Malik, P. K. Kalra
A Generalized Neuron Based Pss In A Multi-Machine Power System, D. K. Chaturvedi, O. P. Malik, P. K. Kalra
D. K. Chaturvedi Dr.
An artificial neural network can work as an intelligent controller for nonlinear dynamic systems through learning, as it can easily accommodate the nonlinearities and time dependencies. In dealing with complex problems, most common neural networks have some drawbacks of large training time, large number of neurons and hidden layers. These drawbacks can be overcome by a nonlinear controller based on a generalized neuron (GN) which retains the quick response of neural net. Results of studies with a GN-based power system stabilizer on a five-machine power system show that it can provide good damping over a wide operating range and significantly …
Experimental Studies Of Generalized Neuron Based Power System Stabilizer, D. K. Chaturvedi, O. P. Malik, P. K. Kalra
Experimental Studies Of Generalized Neuron Based Power System Stabilizer, D. K. Chaturvedi, O. P. Malik, P. K. Kalra
D. K. Chaturvedi Dr.
Artificial neural networks (ANNs) can be used as intelligent controllers to control nonlinear, dynamic systems through learning, which can easily accommodate the nonlinearities and time dependencies. However, they require large training time and large number of neurons to deal with complex problems. To overcome these drawbacks, a generalized neuron (GN) has been developed that requires much smaller training data and shorter training time. Taking benefit of these characteristics of the GN, a new power system stabilizer (PSS) is proposed. Results show that the proposed GN-based PSS can provide a consistently good dynamic performance of the system over a wide range …