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An Online Observer for Minimization of Pulsating Torque in SMPM Motors.

Roșca L, Duguleană M - PLoS ONE (2016)

Bottom Line: Either the motor design or the motor control needs to be improved in order to minimize the periodic disturbances.The compensating signal is identified and added as feedback to the control signal of the servo motor.Compensation is evaluated for different values of the input signal, to show robustness of the proposed method.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Engineering, University "Lucian Blaga" of Sibiu, Sibiu, Romania.

ABSTRACT
A persistent problem of surface mounted permanent magnet (SMPM) motors is the non-uniformity of the developed torque. Either the motor design or the motor control needs to be improved in order to minimize the periodic disturbances. This paper proposes a new control technique for reducing periodic disturbances in permanent magnet (PM) electro-mechanical actuators, by advancing a new observer/estimator paradigm. A recursive estimation algorithm is implemented for online control. The compensating signal is identified and added as feedback to the control signal of the servo motor. Compensation is evaluated for different values of the input signal, to show robustness of the proposed method.

No MeSH data available.


Block diagram of compensation loop.
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pone.0153255.g001: Block diagram of compensation loop.

Mentions: Several studies focused on online estimation methods. I.e. in [4], researches successfully modeled the dynamic voltage behavior of a lithium-ion battery, based on the recursive least square algorithm. The state of charge of a lithium-ion battery was also estimated online using Kalman filter and its variations in [5, 6, 7]. In our case, the compensation requires online parameter identification of the periodic disturbances model, as the disturbing harmonics are sensitive to initial conditions of the rotary motion. For this approach, an adaptive filter based on look-up tables and a recursive estimation algorithm are designed and implemented. The filter is able to eliminate the detected harmonics from the motor current, which contributes to the reduction of developed torque pulsation, for any motor velocity. The recursive estimation algorithm implemented based on the normalized gradient identifies the model parameters. The compensating signal is directly added to the servo motor control signal. The adaptive filter provides the particular disturbing harmonic in the measured motor current during the estimation phase as a function of base rotational frequency. The recursive estimation algorithm implements the normalized gradient method. The estimated disturbance model reshapes the control signal to suppress the disturbing harmonics. The control loop is shown in Fig 1, where u is the control voltage, φ is the angular position, ω is the rotational velocity, i is the motor current and P is the parameters set.


An Online Observer for Minimization of Pulsating Torque in SMPM Motors.

Roșca L, Duguleană M - PLoS ONE (2016)

Block diagram of compensation loop.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835102&req=5

pone.0153255.g001: Block diagram of compensation loop.
Mentions: Several studies focused on online estimation methods. I.e. in [4], researches successfully modeled the dynamic voltage behavior of a lithium-ion battery, based on the recursive least square algorithm. The state of charge of a lithium-ion battery was also estimated online using Kalman filter and its variations in [5, 6, 7]. In our case, the compensation requires online parameter identification of the periodic disturbances model, as the disturbing harmonics are sensitive to initial conditions of the rotary motion. For this approach, an adaptive filter based on look-up tables and a recursive estimation algorithm are designed and implemented. The filter is able to eliminate the detected harmonics from the motor current, which contributes to the reduction of developed torque pulsation, for any motor velocity. The recursive estimation algorithm implemented based on the normalized gradient identifies the model parameters. The compensating signal is directly added to the servo motor control signal. The adaptive filter provides the particular disturbing harmonic in the measured motor current during the estimation phase as a function of base rotational frequency. The recursive estimation algorithm implements the normalized gradient method. The estimated disturbance model reshapes the control signal to suppress the disturbing harmonics. The control loop is shown in Fig 1, where u is the control voltage, φ is the angular position, ω is the rotational velocity, i is the motor current and P is the parameters set.

Bottom Line: Either the motor design or the motor control needs to be improved in order to minimize the periodic disturbances.The compensating signal is identified and added as feedback to the control signal of the servo motor.Compensation is evaluated for different values of the input signal, to show robustness of the proposed method.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Engineering, University "Lucian Blaga" of Sibiu, Sibiu, Romania.

ABSTRACT
A persistent problem of surface mounted permanent magnet (SMPM) motors is the non-uniformity of the developed torque. Either the motor design or the motor control needs to be improved in order to minimize the periodic disturbances. This paper proposes a new control technique for reducing periodic disturbances in permanent magnet (PM) electro-mechanical actuators, by advancing a new observer/estimator paradigm. A recursive estimation algorithm is implemented for online control. The compensating signal is identified and added as feedback to the control signal of the servo motor. Compensation is evaluated for different values of the input signal, to show robustness of the proposed method.

No MeSH data available.