• Proceedings of the Korean Society of Marine Engineers Conference
• /
• 2005.11a
• /
• pp.47-48
• /
• 2005

This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.11a
• /
• pp.95-99
• /
• 1996

The form accuracy of parts has become an important parameter. Therefore dimensional tolerance and geometric tolerance are used in design to satisfy required quility and functions of parts. But the informations for machining conditions, which can satisfy the assigned geometric tolerance in design, are insufficient. The objectives of this research are to study the effects of the grinding parameters such as traverse speed, work speed, depth of cut, and dwell time on the after-ground workpiece shape, and to find out the major parameters among these parameters. Finally, a methodology is proposed for getting the optimal grinding condition for precision workpiece The results are as follows; The effects of work speed and depth of cut on workpiece shape are ignorable compared to the effect of traverse speed. These is the optimal dwell time depending on the traverse speed. The optimal dwell time is decreasing when the traverse speed is increased.

• Journal of Electrical Engineering and information Science
• /
• v.3 no.2
• /
• pp.251-260
• /
• 1998

A DSP-based robust nonlinear speed control of a permanent magnet synchronous motor(PMSM) which is robust to unknown parameter variations and speed measurement error is presented. The model reference adaptive system(MRAS) based adaptation mechanisms for the estimation of slowly varying parameters are derived using the Lyapunov stability theory. For the disturbances or quickly varying parameters. a quasi-linearized and decoupled model including the influence of parameter variations and speed measurement error on the nonlinear speed control of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller to improve the robustness and performance of the nonlinear speed control of a PMSM is designed and compared with the conventional controller. To show the validity of the proposed control scheme, simulations and experimental works are carried out and compared with the conventional control scheme.

• Proceedings of the KSR Conference
• /
• 2008.11b
• /
• pp.874-882
• /
• 2008

In a domestic, HSR-350x which has the maximum speed 350km/h was developed and then next, the next generation high speed train which has the maximum speed 400km/h has still been developing. With developing the next generation high speed railway, there need to be a general plan to make sure of dynamic safety though the a study on the crack and failure of rail by rolling contact fatigue. Therefore, this study investigated occurring stress of rail according to the track quality, train velocity, wheel radius, track stiffness, distance between sleepers, axial force using Eisenmann's equations. For the more, via the finite element method, it investigated shear force on the rail head which could be changed by the early crack length, angle and temperature. As a result, this study confirmed the main elements which effect on the fatigue life cycle of rail.

• Proceedings of the KIEE Conference
• /
• 2003.07b
• /
• pp.1111-1113
• /
• 2003

This paper proposes an effective self-turning algorithm based on Artificial Neural Network (ANN) for fuzzy speed control of the indirect vector controlled induction motor. Indirect vector control method divides and controls stator current by the flux and the torque producing current so that the dynamic characteristic of induction motor may be superior. However, if motor parameter changes, the flux current and the torque producing one's coupling happens and deteriorates the dynamic characteristic. The fuzzy speed controller of an induction motor has the robustness over the effect of this parameter variation than a conventional PI speed controller in some degree. This paper improves its adaptability by adding the self-tuning mechanism to the fuzzy controller. For tracking the speed command, its membership functions are adjusted using ANN adaptation mechanism. This adaptability could be embodied by moving the center positions of the membership functions. Proposed self-tuning method has wide adaptability than existent fuzzy controller or PI controller and is proved robust about parameter variation through Matlab/Simulink simulation.

• Proceedings of the KSME Conference
• /
• 2001.06b
• /
• pp.571-577
• /
• 2001

In this paper, the dynamic response of the pantograph system that supplies electrical power to a high-speed rail vehicle were investigated. The analyses of the catenary based on the Finite Element Method (FEM) is executed to develop a pantograph fits well in high-speed focused on the dynamic characteristic analysis of the pantograph system. By simulation of the pantograph-catenary system, the static deflection of the catenary, the stiffness variation in contact lines, the dynamic response of the catenary undergoing constant moving load and the contact force analysis were executed. By the pantograph-catenary analysis, the design parameters of a pantograph could be optimized. For more improving the dynamic characteristics of the pantograph, the active-pantograph was investigated by controlling a contact force. The active pantograph showed the better performance compared to the parameter-optimized. However, the parameter-optimized pantograph would be acceptable for a high-speed rail vehicle through the design-parameter analysis.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1168-1172
• /
• 2004

This paper presents a speed controller based on an adaptive fuzzy algorithm for high performance permanent magnet synchronous motor (PMSM) drives under parameter and load variations. In many speed tracking control systems PI controller has been used due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, the PI controller parameters are modified during operation by adaptive fuzzy method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.2
• /
• pp.347-352
• /
• 2016

This paper investigates the application, design and implementation of unscented Kalman filter observer using the various scaling parameters for the sensorless speed control of a permanent magnet synchronous motor. The principles of unscented transformation and unscented Kalman filter are examined and their applications are explained. Typically the mapping transformation process is divided into two types, namely the basic unscented transformation and the general unscented transformation by virtue of the scaling parameter value. And resultantly, the number of sampling points, weights, code configuration and computation time are different. But there is no little information on the scaling parameter value or how this value influences the system performance. To analyze the unscented transformation with the various scaling parameters in this study, the experimental results under a wide range of operation condition have been demonstrated.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.111.1-111
• /
• 2001

In this paper, a robust speed control is proposed for Permanent Magnet Synchronous Motor system. PMSM without reduction gear has been widely used in high performance application such as robots and machine tools. It is well known that the control performance of the PMSM is very sensitive to load disturbance and system parameter variation. The idea of the proposed speed controller based on combination of sliding mode control with fuzzy gain scheduling. The sliding mode controller leads to fast system dynamics of slight sensitivity to the load disturbance and system parameter variations, the fuzzy gain scheduling mechanism reduces the chattering phenomenon. The simulation results have proved that the proposed control scheme provides a robust control performance under load disturbance and system parameter variation.

• Proceedings of the KSR Conference
• /
• 2010.06a
• /
• pp.1006-1010
• /
• 2010

This paper discusses the numerical study on the stability of the high-speed EMU by developing its lumped parameter model including the effect of the creepage. The 6, 10 and 14 degrees-of-freedom (DOF) lumper parameter dynamic models are developed and the critical hunting speeds calculated from each model via Matlab software are analyzed and compared. It is demonstrated that the critical hunting speeds decrease while the degrees-of-freedom increase. In addition, the parametric study is conducted to extract major design parameters to influence on the stability of the high-speed EMU.