• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.285-288
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• 2002

This paper presents external load disturbance compensation 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 deadbeat observer To reduce of the noise effect, the post-filter, which is implemented by MA process, is adopted. 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 load 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, are shown in this paper.

• Korean Membrane Journal
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• v.5 no.1
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• pp.36-42
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• 2003

A Prediction of pervaporation performance was studied by solubility parameter calculation approach for the benzene/cyclohexane mixture system using rubbery blend membrane with various solubility parameters. The solubility parameter of the rubbery blend membranes were controlled with different blend ratio of the poly(acrylonitrile-co-butadiene), poly(styrene-co-butadiene) and poly(vinyl chloride). Screening of blend formulations was accomplished by simple swelling tests. When the content of NBR is increased, the swelling of both benzene and cyclohexane are decreased. However, the ratio of benzene swelling to swelling by cyclohexane (the swelling selectivity) increases. The same is true for blends in which the PVC content is increased. Adoption of a solubility parameter calculation provides an a priori methodology for seeking the best blend formulation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.3
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• pp.118-126
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• 2002

AVR parameter tuning for voltage control of generators has generally been done with the off-line open-circuit model of the synchronous generator. When the generator is connected on-line and operating with load the AVR operates in an entirely different environment from the open-circuit conditions. This paper describes a new method for AVR parameter tuning for on line conditions using SQP(Sequential Quadratic Programming) meshed with frequency response characteristics of linearized on-line system model. As the proposed method uses the un - line system model the tuned parameter sets show more optimal behavior in the on-line operating conditions. furthermore, as this method considers the performance indices that are needed for stable operation as constraints, AVR parameter sets that are tuned by this method could guarantee the stable performance, too.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.389-392
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• 2001

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, are shown in this paper.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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• pp.33-39
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• 2019

We propose a mechanical parameter estimation algorithm for surface-mounted permanent magnet synchronous motors (SPMSMs) using a sliding-mode observer (SMO) and an adaptive filter. The SMO estimates system disturbances in real time, which contain the information on mechanical parameters. A desirable feature that distinguishes the proposed estimation algorithm from other existing mechanical parameter estimators is that the adaptive filter estimates electromagnetic torque to improve the estimation performance. Moreover, the SMO acts as a low-pass filter to suppress the chattering effect, which enables the smooth output signals of the SMO. We verify the mechanical parameter estimation performance for SPMSM by conducting extensive experiments for the proposed algorithm.

• Journal of KSNVE
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• v.10 no.4
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• pp.575-583
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• 2000

In this paper, we design a vibration control system that includes a 3-D.O.F. mass-spring-damper structure for the analytical model of a building that is excited at the base of this structure by an external dynamic force, and one Active Mass Damper(AMD) on the top of this structure to generate control forces fro attenuation of the structural response. Two robust controllers based on $\mu$-synthesis and H$\infty$ optimal control are designed for the structural system to show that the performance of a control system can be degraded by some parameter uncertainties such as mass, stiffness coefficients, and/or damping coefficients. The performance of the two controllers are compared in terms of nominal performance, robust stability and robust performance by simulations.

• 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.

• Particle and aerosol research
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• v.18 no.3
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• pp.61-68
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• 2022

In this study, a fluidized bed particle generator was developed to generate an aerosol without supply of compressed air and to increase portability. It was assumed that the mixing ratio of the test particles and beads, the input amount, and the air flow rate supplied to the generator would have effect on the aerosol generation characteristics. The product of these three parameters was set as a characteristic parameter and particle generation characteristics according to the change of the characteristic parameter were observed. As a result, it was confirmed that the input amount of test particles and beads was not suitable as a characteristic parameter and a characteristic parameter expressed as a product of the mass mixing ratio and the air flowrate was newly defined. When the new characteristic parameter is applied, it can be confirmed that the total amount of particles generated from the particle generator is a function of the characteristic parameter. As a result of measuring the amount of particle generation by adjusting the characteristic parameter, it was confirmed that the performance required for the test particle generator for the field inspection equipment of PM-2.5 sensors could be satisfied.

• Journal of Korean Association for Spatial Structures
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• v.17 no.4
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• pp.123-132
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• 2017

A smart tuned mass damper (TMD) was developed to provide better control performance than a passive TMD for reduction of earthquake induced-responses. Because a passive TMD was developed decades ago, optimal design methods for structural parameters of a TMD, such as damping constant and stiffness, have been developed already. However, studies of optimal design method for structural parameters of a smart TMD were little performed to date. Therefore, parameter studies of structural properties of a smart TMD were conducted in this paper to develop optimal design method of a smart TMD under seismic excitation. A retractable-roof spatial structure was used as an example structure. Because dynamic characteristics of a retractable-roof spatial structure is changed based on opened or closed roof condition, control performance of smart TMD under off-tuning was investigated. Because mass ratio of TMD and smart TMD mainly affect control performance, variation of control performance due to mass ratio was investigated. Parameter studies of structural properties of a smart TMD was performed to find optimal damping constant and stiffness and it was compared with the results of optimal passive TMD design method. The design process developed in this study is expected to be used for preliminary design of a smart TMD for a retractable-roof spatial structure.