Design and Modeling of Speed Sensorless Control of DC Motor Drive System

Abstract

Sensorless speed control of a separately excited DC motor using Artificial Neural Network (ANN) technique based on current sensor alone is appliedin this paper. The speed sensorlesssystem based on ANN is estimatedadaptively to overcoming mechanical and physical problems associated with traditional speed sensor. The power circuit of the DC drive system consists of four-quadrant DCchopper 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 reconstructedterminal 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 circuitis designed, evaluated and modelledby 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 effectivenessand successful of the control system, fairly good responseand acceptable agreement between the actual, estimated and desired speeds.