AN ARTIFICIAL NEURAL-NETWORK-BASED IDENTIFICATION AND CONTROL APPROACH FOR THE FIELD-ORIENTED INDUCTION-MOTOR

In this paper, a high-performance speed control approach using artificial neural networks (ANNs) for the field-oriented induction motor is proposed. By using the proposed approach, the speed of an induction motor can be controlled to follow an arbitrarily selected speed trajectory. In particular, an accurate tracking of the speed can still be obtained when uncertainties in the motor and its load exist. The uncertainties include both the unknown load on the motor and the variation of the motor rotor resistance due to temperature change. Two ANNs have been designed to handle these two types of uncertainties. A series of computer simulations has been performed to evaluate the proposed control system. Simulated results show that the proposed control system can achieve satisfactory performances in the tracking of the speed trajectory and the adaptability to rotor resistance parameter variation.