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An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
Published on: March 10, 2011
Indirect adaptive control for synchronous generator: comparison of MLP/RBF neural networks approach with Lyapunov
Jung-Wook Park1, Ronald G Harley, Ganesh K Venayagamoorthy
1Georgia Institute of Technology, Atlanta, GA 30332, USA. jungwookpark@ieee.org
Abstract:
This paper compares two indirect adaptive neurocontrollers, namely a multilayer perceptron neurocontroller (MLPNC) and a radial basis function neurocontroller (RBFNC) to control a synchronous generator. The different damping and transient performances of two neurocontrollers are compared with those of conventional linear controllers, and analyzed based on the Lyapunov direct method.
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