An Interior Point Algorithm for Parameter Estimation of a Geared PMDC Motor Using Current and Speed Step Responses

In this paper, the parameters of the geared PMDC motor are estimated using the interior point algorithm (IPA). The problem of parameter estimation is converted to an optimization problem. The proposed estimation method measures the current and speed responses of the motor under a step input voltage. The objective of the IPA is to search for the parameters of the simulated PMDC motor in order to minimize the errors between the measured current and speed responses of the PMDC motor and the corresponding responses from the simulated model of the PMDC motor. Steady-state mathematical relations between the geared PMDC motor parameters are derived and used as equality and inequality constraints for constructing the proposed IPA. The proposed IPA is a gradient-based optimization algorithm. Therefore, it can efficiently and quickly minimize the objective function and obtain the solution. Moreover, the proposed estimation algorithm considers the estimation of the Coulomb friction torque of the motor. Hence, seven parameters of the geared PMDC motor are estimated: armature resistance, armature inductance, back EMF constant, torque constant, moment of inertia, viscous friction, and Coulomb friction torque. MATLAB and Arduino IDE software are utilized with the Pololu 25D motor for programming and simulation. The experimental setup is used to obtain the measured current and speed step responses. MATLAB and Simulink are used for modeling the simulated PMDC motor and the implementation of the IPA. Simulation and experimental results express the effectiveness of the proposed estimation algorithm in estimating the geared PMDC motor parameters.