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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.
This paper deals with the discrete-time adaptive output trajectory tracking for induction motors in presence of bounded disturbances. A recurrent high order neural network structure is used to design a nonlinear observer and based on this model, a discrete-time control law is derived, which combines discrete-time block control and sliding modes techniques. The paper also includes the respective stability...
This paper presents a discrete-time decentralized control scheme for identification and trajectory tracking of a five degrees of freedom (DOF) robot manipulator. A recurrent high order neural network (RHONN) structure is used to identify the robot model, and based on this model a discrete-time control law is derived, which combines discrete-time block control and sliding modes techniques. The neural...
This paper deals with the adaptive tracking problem for discrete-time induction motor model in presence of bounded disturbances. In this paper, a high order neural network structure is used to identify the plant model and based on this model, a discrete-time control law is derived, which combines discrete-time block control and sliding modes techniques. The paper also includes the respective stability...
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