DC Motor Identification using Impulse Response Data

DC motors are widely used in mechatronic systems. The identification behavior for such motors is of interest. The motor torque and angular velocity outputs are dependant on the voltage and current inputs. This relationship is governed by the motor characteristics such as inductance, resistance, moment of inertia, friction, load, and motor constants. In this paper, impulse response data is used to identify the motor transfer function with voltage as input and angular speed as output. An auto regressive moving average (ARMA) model with a steepest descent algorithm was used to minimize the error between the original and modeled velocities. Once the ARMA model was constructed, the transfer function was realized. Then the input voltage was varied and the identified model results where compared with the original system