Application of RBF Network in Rotor Time Constant Adaptation

P. Brandstetter, P. Chlebis, P. Palacky, O. Skuta


The paper presents the results of the rotor time constant adaptation method with the application of artificial neural network. Theestimation of the rotor time constant for adaptive model of MRAS is realized by the help of PI-controller and then is replaced by theRadial Basis Function network. The estimated rotor time constant is then used in the vector control of electrical drive. There werediscussed the different architectures of RBF network in the field of adaptation of rotor time constant parameter. Simulations have beenperformed in the Matlab-Simulink. Ill. 20, bibl. 8 (in English; abstracts in English and Lithuanian).

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