Design and modeling of speed sensorless control of DC motor drive system

Abstract EN

-Sensorless speed control of a separately excited DC motor using Artificial Neural Network (ANN) technique based on current sensor alone is applied in this paper.

The speed sensorless system based on ANN is estimated adaptively to overcoming mechanical and physical problems associated with traditional speed sensor.

The power circuit of the DC drive system consists of four-quadrant DC chopper with MOSFET transistors and reverse diodes.

The ANN is trained, as a model adaptive reference system method, to estimate speed of the DC motor based on armature current sensor of the drive circuit and reconstructed terminal voltage waveform, which is generate depending on the PWM pulses of the DC chopper, as ANN inputs.

The DC drive controller consists of proportional-integral controller, logic gates and routing circuits beside the trained ANN.

The DC drive circuit is designed, evaluated and modelled by Matlab/Simulink in the forward and reverse motoring operation modes, respectively.

The DC drive system is simulated at different speed variation in steady state and dynamic operating conditions.

The simulation results without speed sensor illustrate the effectiveness and successful of the control system, fairly good response and acceptable agreement between the actual, estimated and desired speeds