Real-time output tracking for induction motors by recurrent high-order neural network control

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 analysis, for the whole system with a strategy to avoid specific adaptive weights zero-crossing. Applicability of the scheme is illustrated via experimental results in real-time for a three phase induction motor.