Adaptive neural network-based state filter for induction motor speed estimation

Effective sensorless speed estimation is desirable for both online condition monitoring of induction motors and sensorless adjustable speed AC drive applications. In this paper, the authors present a neural network-based sensorless adaptive speed filter for induction motors. In addition to nameplate information required for the initial set-up, the proposed neural network-based speed filter uses only actual motor currents and voltages. The initial training of the filter helps in obtaining quite acceptable transient speed response from the estimation algorithm. The paper demonstrates the feasibility of adaptive speed filtering for induction motor which could be used for both diagnosis and control purposes.