• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.26-28
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• 2009

This paper proposes maximum torque control of IPMSM drive using adaptive teaming mechanism-fuzzy neural network (ALM-FNN) controller, model reference adaptive fuzzy tonal(MFC) and artificial neural network(ANN). This control method is applicable over the entire speed range which considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using ALM-FNN, MFC and ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN, MFC and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN, MFC and ANN controller.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.159-162
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• 2001

This paper is proposed an efficiency optimization operation algorithm for synchronous reluctance motor (SynRM) using current phase angle control technique. The SynRM has to controlled with the optimal current phase angles with load and operation speed variation, to obtain high efficiency over the wide speed ranges. An efficiency optimization condition in SynRM which minimizes the copper and iron losses is derived based on the equivalent circuit model of the machine. The objective of the efficiency optimization control algorithm compensating the optimum current angle, is to seek a combination of d and q-axis current components which provides minimum losses at a certain operating point in steady state. The usefulness of the proposed efficiency optimization control is verified through vector-controlled inverter system with the SynRM.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1080-1087
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• 2009

This paper presents an algorithm to acquire 3D geometric information using a virtual plane method. The method to measure 3D information on the plane is easy, because it's not concerning value on the z-axis. A plane can be made by arbitrary three points in the 3D space, so the algorithm is able to make a number of virtual planes from feature points on the target object. In this case, these geometric relations between the origin of each virtual plane and the origin of the target object coordinates should be expressed as known homogeneous matrices. To include this idea, the algorithm could induce simple matrix formula which is only concerning unknown geometric relation between the origin of target object and the origin of camera coordinates. Therefore, it's more fast and simple than other methods. For achieving the proposed method, a regular pin-hole camera model and a perspective projection matrix which is defined by a geometric relation between each coordinate system is used. In the final part of this paper, we demonstrate the techniques for a variety of applications, including measurements in industrial parts and known patches images.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.4
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• pp.240-246
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• 2018

In this paper, a sensorless V/f control based on maximum torque per ampere (MTPA) operation for PMSMs is proposed. Given that the MTPA operation is not considered in the conventional sensorless V/f control, efficient PMSM drives cannot be achieved. Therefore, this paper proposes an improved technique based on the d-axis current control to enable the MTPA operation in the V/f control for PMSMs. A stabilization technique is also proposed to improve the dynamic characteristics and stability against load variation. The effectiveness of the proposed technique is verified by conducting experiments with a 250 W SPMSM for driving a blower.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.52 no.1
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• pp.1-8
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• 2003

The paper proposes instantaneous torque control of IPMSM for maximum torque drive of torque and current plane. The control scheme is based on the mathematical model of the motor and is applicable to the constant torque and field weakening operations. The scheme allows the motor to be driven with maximum torque per ampere(MTPA) characteristic below base speed and it maintains the maximum voltage limit of the motor wide field weakening and the motor current limit under all conditions of operation accurately. For each control mode, a condition that determines the optimal d-axis current $^id$ for maximum torque operation is derived. The proposed control algorithm is applied to IPMSM drive system for drive of wide speed range, the operating characteristics controlled that maximum torque control are examined in detail by simulation.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.386-393
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• 2008

A position control method for interpolating aspherical grinding and polishing tool path was reviewed and experimented in a nano precision machine. The position-base algorithm was reformed from the time-base algorithm, proposed in the previous study. The characteristics of the algorithm were in the velocity control loop with position feedback. The aspherical surface was divided by an interval at which each velocity and acceleration were calculated. The theoretical velocity was corrected by position error during processing. In the experiment, a machine was constructed and nano-scale linear encoders were installed at each axis. Relation between process parameters and the variation of position error was monitored and discussed. The best result from optimized parameters showed that the accuracy was 150nm and improved from the previous report.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.956-957
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• 2008

The paper is proposed maximum torque control of SynRM drive using Multi-PI controller. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current ids for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled Multi-PI controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the Multi-PI controller.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.219-220
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• 2008

The paper is proposed maximum torque control of SynRM drive using adaptive fuzzy neuro inference system(AFNIS) and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled AFNIS and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the AFNIS and ANN controller.

• Proceedings of the KIEE Conference
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• 2006.04b
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• pp.155-157
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• 2006

The paper is proposed maximum torque control of SynRM drive using adaptive learning mechanism-fuzzy neural network(ALM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.198-201
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• 2005

The paper is proposed maximum torque control of IPMSM drive using adaptive learning mechanism-fuzzy neural network (ALM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $^i_d$ for maximum torque operation is derived. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verily the effectiveness of the ALM-FNN and ANN controller.