• Journal of Power Electronics
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• v.16 no.1
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• pp.1-8
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• 2016

Dead time is typically incorporated in voltage source inverter systems to prevent short circuit cases. However, dead time causes an error between the output voltage and reference voltage. Hence, voltage equation-based algorithms, such as motor parameter estimation and back electromotive force (EMF)-based sensorless algorithms, are prone to estimation errors. Several dead-time compensation methods have been developed to reduce output voltage errors. However, voltage errors are still common in zero current crossing areas, and an effect of the error is much worse in a low speed region. Therefore, employing voltage equation-based algorithms in low speed regions is difficult. This study analyzes the conventional dead-time compensation method and output voltage errors in low speed operation areas. A current shaping method that can reduce output voltage errors is also proposed. Experimental results prove that the proposed method reduces voltage errors and improves the accuracy of the parameter estimation method and the performance of the back EMF-based sensorless algorithm.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.3
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• pp.188-195
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• 2004

This paper presents neural load torque observer that is used to deadbeat load torque observer and gain compensation by parameter estimator As a result, the response of the PMSM(permanent magnet synchronous motor) follows that nominal plant. The load torque compensation method is composed of a neural deadbeat observer To reduce the noise effect, the post-filter implemented by MA(moving average) process, is adopted. The parameter compensator with RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller The parameter estimator is combined with a high performance neural load torque observer to resolve the problems. The neural network is trained in on-line phases and it is composed by a feed forward recall and error back-propagation training. During the normal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against the load torque and the Parameter variation. A stability and usefulness are verified by computer simulation and experiment.

• Journal of Power Electronics
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• v.8 no.4
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• pp.354-362
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• 2008

This paper presents neural load torque compensation method which is composed of a deadbeat load torque observer and gains compensation by a parameter estimator. As a result, the response of the PMSM (permanent magnet synchronous motor) obtains better precision position control. To reduce the noise effect, the post-filter is implemented by a MA (moving average) process. The parameter compensator with an RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural load torque observer to resolve problems. The neural network is trained in online phases and it is composed by a feed forward recall and error back-propagation training. During normal operation, the input-output response is sampled and the weighting value is trained multi-times by the error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against load torque and parameter variation. Stability and usefulness are verified by computer simulation and experiment.

• Smart Structures and Systems
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• v.25 no.5
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• pp.569-580
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• 2020

The identification of delays and delay compensation are critical problems in real-time hybrid simulations (RTHS). Conventional delay compensation methods are mostly based on the assumption of a constant delay. However, the system delay may vary during tests owing to the nonlinearity of the loading system and/or the behavioral variations of the specimen. To address this issue, this study presents an adaptive delay compensation method based on a discrete model of the loading system. In particular, the parameters of this discrete model are identified and updated online with the least-squares method to represent a servo hydraulic loading system. Furthermore, based on this model, the system delays are compensated for by generating system commands using the desired displacements, achieved displacements, and previous displacement commands. This method is more general than the existing compensation methods because it can predict commands based on multiple displacement categories. Moreover, this method is straightforward and suitable for implementation on digital signal processing boards because it relies solely on the displacements rather than on velocity and/or acceleration data. The virtual and real RTHS results show that the studied method exhibits satisfactory estimation smoothness and compensation accuracy. Furthermore, considering the measurement noise, the low-order parameter models of this method are more favorable than that the high-order parameter models.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.2
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• pp.75-82
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• 1999

A compensation method of the motor parameters using zero sequence third harmonic voltage is presented for the speed sensorless vector control of the induction motor considering saturation of the flux. Generally, the air-gap flux of the saturated induction motor contains the space harmonic components rotating with the synchronous frequency of the motor. Because the EMF of the saturated induction motor contains the zero sequence harmonic voltages at the neutral point of the motor, those harmonic voltages can be used as a saturation index. In this work, the rotor flux observer is firstly designed for the speed sensorless vector control of induction motor. And a novel measurement method of the space harmonic voltage and a compensation method of th LPF(Low Pass Filter) are proposed. For compensating the non-linear variations of the magnetizing inductance depending on the saturation level of the motor, the dominant third harmonic voltage of the motor is used as a saturation function of the air-gap flux. And the variation of the stator resistance owing to the motor temperature can also be measured with the phase angle between the impressed voltage vector and the zero sequence voltage. The validity of the proposed parameter compensation scheme in the speed sensorless vector control using rotor flux observer is verified by the result of the simulations and the experiments.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.10
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• pp.573-580
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• 2002

This paper presents neural load disturbance observer that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a neural deadbeat observer. To reduce of the noise effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM(recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. The proposed estimator is combined with a high performance neural torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation and experiment, are shown in this paper.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.1
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• pp.29-37
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• 2012

A simple and effective dead time compensation scheme for a PWM inverter-fed permanent magnet synchronous motor (PMSM) drive using the model reference adaptive control (MRAC) and coordinate transformation is presented. The basic concept is to first transform a time-varying disturbance caused by the dead time and inverter nonlinearity into unknown constant or slowly-varying one by the coordinate transformation, and then use the MRAC design technique to estimate this parameter in the stationary reference frame. Since the MRAC scheme is a suitable way of estimating such a parameter, the control performance can be significantly improved as compared with the conventional observer-based method tracking time-varying parameters. In the proposed scheme, the disturbance voltage caused by the dead time is effectively estimated and compensated by on-line basis without any additional circuits nor existing disadvantages as in the conventional methods. The asymptotic stability is proved and the effectiveness of the proposed scheme is verified.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.379-386
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• 2013

The hemispherical resonator gyroscope is a type of vibratory gyroscope, which can measure angle or angular rate, based on its operating mode. This paper deals with the case when the hemispherical resonator gyroscope is operated in angle measurement mode. In angle measurement mode, the resonator pattern angle precesses, with respect to the external rotation input, by the principle of the Coriolis effect, so that the external rotation can be estimated, by measuring the amount of precession angle. However, this pattern angle drifts, due to the manufacturing error of the resonator. Since the drift effect causes degradation of the angle estimation performance of the resonator, the corresponding drift compensation control should be performed, to enhance the estimation performance. In this paper, a mathematical model of the hemispherical resonator gyro is first introduced. By using the mathematical model, a nonlinear observer for imperfection parameter estimation, and the corresponding compensation controller are designed to operate hemispherical resonator gyros, as angle measurement sensors.

• Journal of IKEEE
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• v.25 no.2
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• pp.261-266
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• 2021

This paper suggests design methodology for thermal infrared data correction algorithms considering environmental temperature variations. First, a thermal infrared measurement model is suggested by a parameter-dependent first-order input-output equation using the relationship between infrared measurement data and model environmental parameters. In order to compensate the influence of environmental temperatures on infrared data, a compensation function is identified. Through experiments, the proposed algorithm is shown to reduce the influence of environmental temperatures on the infrared data effectively.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1820-1825
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• 2005

DSP chip parameters of a digital hearing aid (HA) should be optimally selected or fitted for hearing impaired persons. The more precise parameter fitting guarantees the better compensation of the hearing loss (HL). Digital HAs adopt DSP chips for more precise fitting of various HL threshold curve patterns. A specific DSP chip such as Gennum GB3211 was designed and manufactured in order to match up to about 4.7 billion different possible HL cases with combination of 7 limited parameters. This paper deals with a digital HA fitting program which is developed for optimal fitting of GB3211 DSP chip parameters. The fitting program has completed features from audiogram input to DSP chip interface. The compensation effects of the microphone and the receiver are also included. The paper shows some application examples.