A robust speed and ann sensorless induction motor drives

Abstract EN

This paper deals with the synthesis of a robust H..

Loop shaping control for a sensor less induction motor (IM) drive.

The designed H...

Controller id a SISO (Single Input Single Output) feedback controller and is used in combination with a direct field oriented control (DFOG).

In industrial applications, the classical regulation methods are widely used because their structure is simple, tuning parameters are fewer, and they are lower order.

Their drawbacks are those control parameters are difficult to tune for high performance and the lack robustness.

Thus, for overcoming already quoted restrictions, the use of the H...

Loop shaping approach has been considered as an attractive prospect.

The infinity norm of transfer function from disturbance to states is minimized via search and weights evolutionary computation.

In this paper, the artificial neural network (ANN) is used to estimate the induction motor speed.

The ANN estimator is trained offline by using the error back propagation algorithm, and its output is then fed back in the speed control loop.

Hence, the speed sensor less IM drive is achieved.

The proposed sensor less control scheme is robust against load torque disturbance and parameter variations.

It also ensures a precise trajectory tracking with the prescribed dynamic.

The simulation results demonstrate the effectiveness of the proposed IM sensor less control scheme.