Field oriented control for three phase induction motor based on full neural estimator and controller

Abstract EN

Closed loop speed control for an I.

M is somewhat complex strategy, the complexity is gradually increases according to the demand performance degree.

There are many types of control strategies : scalar, direct torque, adaptive, sensor less, and vector or Field Oriented Control (FOC).

This paper proposes the FOC strategy in details.

Rotor flux, unit vector, and electromagnetic torque estimation are considered by using Digital Signal Processing (DSP).

Artificial Neural Network (ANN) becomes a powerful tool for control nonlinear system in present time.

This study proposes the using of ANN in stead of DSP to estimate the flux, unit vector, and electromagnetic torque to reduce the hardware complexity and the Electromagnetic Interference (EMI) effect.

Also, it proposes the PI neural-based controller.

The overall system simulation for both DSP and ANN are proposed.

The performances of both systems are investigated, which give in DSP : rise time 0.24 sec, settling time 0.29 sec, overshot 5 %, steady state error 0.5 %.

Whereas, in ANN : rise time 0.18, settling time 0.19 sec, overshot 1 %, steady state error 0.2 %.