• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.1
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• pp.18-25
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• 2013

In this paper, a nonlinear controller based on adaptive back-stepping method is proposed for high performance operation of Interior Permanent Magnet Synchronous Motor (IPMSM). First, in order to improve the performance of speed tracking, a nonlinear back-stepping controller is designed. In addition, since it is difficult to achieve the high quality control performance without considering parameter variation, a parameter estimator is included to adapt to the variation of load torque in real time. Finally, for the efficiency of power consumption of the motor, controller is designed to operate motor with the minimum current for the required maximum torque. The proposed controller is tested through experiment with a 1-hp Interior Permanent Magnet Synchronous Motor (IPMSM) for the angular velocity reference tracking performance and load torque volatility estimation, and to test the Maximum Torque per Ampere (MTPA) operation. The result verifies the efficacy of the proposed controller.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.3
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• pp.195-203
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• 2000

In this paper a new controller is proposed to operate the interior permanent magnet synchronous motor(IPMSM) by the control method of the maximum torque per ampere in constant torque region. The implementation method of the conventional torque controller is explained and analyzed exactly. The proposed controller does not use the torque and q-axis current of the speed controller but the amplitude of the stator current in order to utilize not only the magnetic alignment torque but also the reluctance in the constant region, gurantees the linearity of the torque, and is easily implemented. These attractive are verified through the experiment.

• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.5
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• pp.16-28
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• 2010

This paper proposes maximum torque control of SynRM drive using artificial intelligent(AI)PI 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 axis current for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled AIPI and ANN controller and the operating characteristics controlled by maximum torque control are examined in detail.

• 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.

• Korean Journal of Applied Biomechanics
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• v.24 no.3
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• pp.309-315
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• 2014

The aim of the present study was to investigate the effects of 6-week wrist resistance training on wrist torque control. Nineteen subjects were randomly assigned to either the wrist training group (n=9) or the control group (n=10). The training group performed wrist exercises for six directions (flexion, extension, pronation, supination, radial deviation, and ulnar deviation) while the control group did not. Testing for the isometric torque control error, one-repetition maximum (1-RM) strength, and isokinetic maximum torque (angular velocity of $60^{\circ}/s$ wrist movements) were conducted before and after six weeks of resistance training and after every two-week interval of training. The wrist training group showed significant decreases in isometric torque control error in all six directions after the 2-week resistance training, while the control group did not show significant increase or decrease. The training group showed significant increases in the maximum strength in all six directions assessed by 1-RM strength and isokinetic strength tests after the 4-week resistance training, while the control group did not show any statistically significant changes. This study shows that motor control ability significantly improves within the first two weeks of resistance training, while the wrist strength significantly improves within the first four weeks of resistance training in wrist training group compared to the control.

• Journal of the Korean Society of Safety
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• v.17 no.2
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• pp.32-38
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• 2002

In this paper, a new approach for the SynRM(Synchronous Reluctance Motor) control which ensures producing MTPA(Maximum Torque per Ampere) over the entire field weakening region is presented. In addition, this paper presents a speed sensorless control scheme of SynRM using flux observer. Also, by adjusting the base speed for the field weakening operation according to the flux level, the current and voltage limit, the smooth and precise transition into the field weakening operation can be achieved. The validity of the proposed scheme is verified through simulation.

• Journal of Oral Medicine and Pain
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• v.24 no.4
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• pp.455-466
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• 1999

The purpose of this study was to investigate the magnitude of mandibular rotational torque movements in subjects with TMJ sounds, and to analyse correlation between quantitative characteristics of TMJ sounds and mandibular rotational torque movement. Twenty dental college students with TMJ clicking and twenty students without any TMD signs and symptoms were examined by mean of SonoPak and Rotate program of BioPAK system(Bioresearch Inc. MilWaukee, wisconsin, USA) in this study. Mandibular rotational torque movements were recorded and analysed during maximum mouth opening, protrusion, and lateral excursion in frontal and horizontal planes. The obtained results were as follows: 1. On maximum mouth opening, mandibular rotational angle and distance of clicking group were significantly greater than those of control group in frontal plane. (P<0.05). 2. During maximum mouth opening closing, maximum mandibular rotational angle and distance of clicking group were significantly greater than those of control group in frontal plane. (P<0.01). 3. On protrusion, mandibular rotational angle and distance of clickin group were significantly greater than those of control group in horizontal plane. (P<0.05). 4. On lateral excursion, there was no significant difference in mandibular rotational angle and distance between clicking group and control group in frontal and horizontal planes. 5. There were significant correlations between peak amplitude of TMJ sounds and maximum mandibular rotational distance during maximum mouth opening (r=-.481) and mandibular rotational distance on maximum mouth opening (r=-.455) in horizontal plane. 6. There were significant correlations between Above 300/(0-300)Hz ratio of TMJ sounds and mandibular rotational angle (r=-.499) and distance (r=-.457) on maximum mouth opening in frontal plane.