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This paper presents a discrete-time adaptive neural backstepping control for a double fed induction generator connected to an infinity bus, based on a discrete-time high order neural network (HONN), which is trained with an extended Kalman filter (EFK) algorithm. The discrete-time adaptive neural backstepping control performance is illustrated via simulations.
In this paper, the authors propose a block control scheme using sliding modes, for a double fed induction generator connected to an infinity bus. To estimate the mechanical torque, a nonlinear observer is utilized; additionally, as a viable alternative, to eliminate the requirement on this estimation, an integrator is included. To reduce the effect of parameter variations, the one step delayed disturbance...
This paper presents neuronal network identification of a double fed induction generator, based on a discrete-time high order neuronal network (RHONN), which is trained with an extended Kalman filter (EFK) algorithm. The neuronal identification performance is illustrated via simulations.
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