• Journal of Power Electronics
• /
• v.17 no.5
• /
• pp.1211-1222
• /
• 2017

In order to decrease the parameter sensitivity of deadbeat direct torque control (DB-DTC), an improved deadbeat direct torque control method for surface mounted permanent-magnet synchronous motor (SPMSM) drives is proposed. First, the track errors of the stator flux and torque that are caused by model parameter mismatch are analyzed. Then a sliding mode observer is designed, which is able to predict the d-q axis currents of the next control period for one-step delay compensation, and to simultaneously estimate the model parameter disturbance. The estimated disturbance of this observer is used to estimate the stator resistance offline. Then the estimated resistance is required to update the designed sliding-mode observer, which can be used to estimate the inductance and permanent-magnetic flux linkage online. In addition, the flux and torque estimation of the next control period, which is unaffected by the model parameter disturbance, is achieved by using predictive d-q axis currents and estimated parameters. Hence, a low parameter sensitivity DB-DTC method is developed. Simulation and experimental results show the validity of the proposed direct control method.

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

• Communications for Statistical Applications and Methods
• /
• v.15 no.5
• /
• pp.655-666
• /
• 2008

Small sample likelihood based inference for the shape parameter of the inverse Gaussian distribution is the purpose of this paper. When shape parameter is of interest, the signed log-likelihood ratio statistic and the modified signed log-likelihood ratio statistic are derived. Hsieh (1990) gave a statistical inference for the shape parameter based on an exact method. Throughout simulation, we will compare the statistical properties of the proposed statistics to the statistic given by Hsieh (1990) in term of confidence interval and power of test. We also discuss a real data example.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.5
• /
• pp.429-433
• /
• 2007

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.15 no.5
• /
• pp.18-24
• /
• 2016

An electromagnetic linear actuator is controlled precisely and securely and is useful in devices that require linear motion. The most commonly used method in the performance verification process for an electromagnetic actuator is finite element analysis that utilizes CAE. However, finite element analysis has the disadvantage that modeling and analysis consume a lot of time. Accordingly, lumped parameter analysis can be an alternative approach to the finite element method because of its computation iteration capability with fair accuracy. In this paper, the lumped parameter model and simulation results are presented. In addition, the results of the lumped parameter analysis are compared with those obtained from finite element analysis for verification.

• Journal of Electrical Engineering and Technology
• /
• v.5 no.4
• /
• pp.597-605
• /
• 2010

This paper presents a contribution to parameter identification of a non-linear system using a new strategy to improve the genetic algorithm (GA) method. Since cost function plays an important role in GA-based parameter identification, we propose to improve the simple version of GA, where weights of the cost function are not taken as constant values, but varying along the procedure of parameter identification. This modified version of GA is applied to the induction motor (IM) as an example of nonlinear system. The GA cost function is the weighted sum of stator current and rotor speed errors between the plant and the model of induction motor. Simulation results show that the identification method based on improved GA is feasible and gives high precision.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.5
• /
• pp.481-486
• /
• 2002

In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-5) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control. Based on the derived design method, the parameter estimation for controllable canonical T-S fuzzy model is also Presented.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.19 no.5
• /
• pp.799-812
• /
• 2017

Backfill grouting and realistic convergence distribution were not properly considered in previous studies on 2D numerical analysis of a shield TBM tunnel. In this study, a modeling method was suggested to cope with this problem by considering a realistic convergence distribution and proper properties of backfill grouting. To this end, the influence of gap parameter and depth of rock cover on volume loss and composed of ground volume loss around tunnel excavation and surface volume loss were analyzed with a single layer of weathered soil. As a result, most of surface settlements were occurred immediately after excavation. Additional, as depth of rock cover and gap parameter increased, the influence range of surface settlement curves obtained from 2D numerical analyses became broader than a suggested theoretical equation. Therefore, it is inferred that gap parameter should be applied based on load distribution ratio and the property of backfill grouting properly considered for the estimation of the precise behavior of a shield TBM tunnel in 2D numerical analysis.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.5
• /
• pp.575-581
• /
• 2007

Though the Hough transform is a well-known method for detecting analytical shape represented by a number of free parameters, the basic property of the Hough transform, the one-to-many mapping from an image space to a Hough space, causes the innate problem, the sensitivity to noise. To remedy this problem, Edge Strength Hough Transform (ESHT) was proposed and proved to reduce the noise sensitivity. However the performance of ESHT depends on the size of a Hough space and image and some other parameters which should be decided experimentally. In this paper, we derived formulae to decide 2 parameter values; decreasing parameter and broadening parameter, which play an important role in ESHT. Using the derived formulae, 2 parameter values can be decided only with the pre-determined values, the size of a Hough space and an image, which make it possible to decide them automatically. The experiments with different parameter values also support the result.

• Journal of applied mathematics & informatics
• /
• v.29 no.5_6
• /
• pp.1257-1268
• /
• 2011

The thermal behavior of wood exposed to the outdoors is influenced by solar absorptivity and longwave emissivity. However, it is difficult to measure that properties directly. Hence we estimate the values of the parameter by using the least-square optimization technique. Finally we report the results for the computation of the values of the parameters.