DocumentCode :
3586653
Title :
Dynamic determination of DC motor parameters - Simulation and testing
Author :
Beloiu, Robert
Author_Institution :
Comput. & Electr. Eng. Dept., Univ. of Pitesti, Pitesti, Romania
fYear :
2014
Firstpage :
13
Lastpage :
18
Abstract :
DC motors are widespread used in modern day applications of different kind, especially those that require a closed loop control. In order to use a DC motor in closed loop control systems, it is required to know the dynamic both electrical and mechanical parameters. Parameter estimation for DC motors, both brushed and brushless, is of equal importance in the field of motor control. Accurate determination of DC motor parameters is vital for a good control. The estimation of parameters could be done using several methods: using hybrid equivalent circuit model, step response, dynamic load variation, closed loop error approach, least square parametric estimation, least-squares approximation technique and a closed-loop disturbance observer. In the present paper, it is studied the dynamic mechanical parameter identification as a response to a step input signal and identified with a 2nd order dynamic system.
Keywords :
brushless DC motors; closed loop systems; equivalent circuits; least squares approximations; load regulation; machine control; observers; parameter estimation; DC motor parameter dynamic determination; brushed DC motor control field; brushless DC motor; closed loop control system; closed loop disturbance observer; closed loop error approach; dynamic load variation; dynamic mechanical parameter identification; electrical parameter estimation; hybrid equivalent circuit model; least square parametric estimation; least squares approximation technique; step response; DC motors; Integrated circuit modeling; Mathematical model; Parameter estimation; Permanent magnet motors; Torque; Vehicle dynamics; DC motor; inertial torque; speed overshoot; transfer function; visous friction coefficient;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Computers and Artificial Intelligence (ECAI), 2014 6th International Conference on
Print_ISBN :
978-1-4799-5478-0
Type :
conf
DOI :
10.1109/ECAI.2014.7090191
Filename :
7090191
Link To Document :
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