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Use the Adaptive Algorithm to Estimate the Reverse Motive Force, Position and Speed of the Motor (BLDC) and Compare with the Gradient Estimation Method based on Parametric Modeling
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 3 |
| Year of Publication: 2021 |
| Authors: Reem Toumi, D. Marwan Jabra Labbad |
10.5120/ijca2021921318
|
Reem Toumi, D. Marwan Jabra Labbad . Use the Adaptive Algorithm to Estimate the Reverse Motive Force, Position and Speed of the Motor (BLDC) and Compare with the Gradient Estimation Method based on Parametric Modeling. International Journal of Computer Applications. 183, 3 ( May 2021), 57-64. DOI=10.5120/ijca2021921318
Abstract
In this paper, the BLDC motor was modeled and then simulated using Simulink in the Matlab program, depending on the BLDC motor representation with state equations, and the transistor inverter that generates a three-phase motor driving signal (BLDC) was also modeled. In order to control the operation of these motors, it requires obtaining the signals of the currents of the three phases of the motor, which requires the use of three sensors (Hall), But these sensors are expensive and their use leads to noise in the current signals, so to avoid using Hall sensors, the signals of the three phase currents were guessed using the predictive algorithm, and in the next stage the BLDC motor was modeled based on parametric modeling which is characterized by obtaining an auxiliary signal. It can be used to estimate the signals of the three phase currents of the motor, and we will use the gradient method of estimating. The adaptive algorithm for estimating the motor signals (BLDC) was compared with the gradient estimation method based on the parametric modeling when there is no load and when the motor axis is loaded with a load. And angular velocity signal, three phase current signals, and position signal.
References
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