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In this paper the torque and the square of the rotor flux magnitude control using second order sliding mode controller for an induction motor, is proposed. Designed super-twisting controller permits to reduce chattering that is inherent in standard sliding mode control and to improve accuracy. To estimate the rotor flux and speed, an adaptive observer is proposed. The effectiveness of the designed...
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.
This paper presents a discrete-time direct current (DC) motor torque tracking controller, based on a recurrent high order neural network (RHONN) to identify the plant model. Using this model, a control law is derived, which combines block control and sliding modes techniques. The applicability of the scheme is illustrated via real time implementation for a DC motor with separate winding excitation.
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...
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