• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.397-400
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• 2001

This paper proposed a speed adaptive control system with load torque observer and feed-forward compensation using neural network for air compressor system driven an induction motor. The motor receive impact load change under the influence of piston movement of up and down, and so it difficult to obtain good speed control characteristics. With real-time adjusting control gain estimated in neural network, control characteristics of motor is improved. The validity of the proposed system is confirmed through the theoretical analysis and computer simulation.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.1123-1133
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• 2012

This study configuration Vector Control System which is stable and has outstanding Dynamic Characteristics in Very Low Speed Region and Low Speed Region, and proposes Instantaneous Speed Observer and Very Low Speed Control method and vector control system of the speed estimation a using Reduced-Dimensional State Observer. The Observer proposed in this system, by appling Reduced-Dimensional State Observer to Load-Torque estimation and using for speed estimation, implements system composition simply and is capable of accurate Instantaneous Speed estimation in Very Low Speed Region. Also, this study reduces influence by System Noise and suggests an induction motor speed control system which is effective in Load Disturbance, modeling error, estimation noise and so on without changing pole of an Observer.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.27-34
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• 2006

This paper proposes a new method of on-line estimation for rotor resistance of the induction motor in the indirect vector controlled drive, using artificial neural network (ANN). The back propagation algorithm is used for training of the neural networks. The error between the desired state variable of an induction motor and actual state variable of a neural network model is back propagated to adjust the weight of a neural network model, so that the actual state variable tracks the desired value. The performance of rotor resistance estimator and torque and flux responses of drive, together with these estimators, are investigated variations rotor resistance from their nominal values. The rotor resistance are estimated analytically, using the proposed ANN in a vector controlled induction motor drive.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.1
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• pp.90-97
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• 2001

In this paper, a novel speed control strategy using an acceleration feedforward compensation by the estimation of the system inertia is proposed. With the proposed method, the enhanced speed control performance can be achieved and the speed response against the disturbance torque can be improved for the vector-controled induction motor drive systems in which the bandwidth of the speed controller cannot be made large enough. The simulation and experimental results for induction motor drive systems confirm the validity of the proposed strategy.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.24-31
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• 2007

This paper presents self tuning PI(STPI) controller of IPMSM drive using neural network. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, STPI controller proposes a new method based neural network. STPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.7
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• pp.65-73
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• 2006

This paper presents speed control of IPMSM drive using neural network(NN) PI controller. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, NNPI controller proposes a new method based neural network. NNPI controller is developed to minimize overshoot rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1092-1099
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• 2006

Displayed system equationally using accurate dynamic modeling of whole system including induction motor and load to analyze induction motor to normal condiction's action characteristic as well as transient characteristic using power converter device such as inverter in this paper. Also, presume adhesive power calculation through speed sensorless vector control and load torque disturbance observer for maximum tractive force control. Confirmed proposed algorithm through simulation and an experiment using railroad experiment equipment to embody control algorithm of such system. With relation of adhesive power about the wage speed by speed addition and subtraction of railway vehicle, embodied all sorts item by experiment equipment.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.3
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• pp.164-172
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• 2004

This paper presents the comparison results of some kinds of control method in circumstance of eccentric load. The plant to be controlled is a computed tomography(CT) driven by a permanent magnet synchronous motor. In a CT system, many units are attached on the rotationally part of a gantry such as x-ray tube, detector, heat exchanger, and data acquisition unit etc. Therefore keeping many components to balance which have different weight is not easy; this is inescapable problem in the all CT systems. To solve this problem against eccentric load, some kinds of control method have been compared and analysed by using protype CT. From the experimental results it is vilified that the CT drive system with model reference control method indicates higher speed regulation ability regardless of variable eccentric weight and uncertain position, and also in the limit condition of constant eccentric weight and fixed position, the compensation method with sinusoidal form is a strong candidate in view of speed ripple reduction.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.1
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• pp.60-68
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• 1999

This paper deals with the tracking control problem of industrial robotic manipulators with unknown or changing dynamics. The proposed method makes use of multiple moodels and switching mechanism by fuzzy inference of the manipulator in an indirect adaptive controller architecture. The models used for the indmtification of the manipliator are identical, except for the initial estimates of the unknown inertial pararmeters of the manipulator and its load. The torque input that is applied to the joint actuators is determined at every instant by the identification model that best approximates the robot dynamics. Simulation results are also included to dermnstrate the improvement in the tracking perfermance when the proposed method is used.s used.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.581-588
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• 2020

This study examined a brake pad wear compensation method for an Electro-Mechanical Brake (EMB) using the braking test device. A three-phase Interior Permanent Magnet Synchronous Motor (IPMSM) was applied to drive the actuator of an EMB. Current control, speed control, and position control were used to control the clamping force of the EMB. The wear compensation method was performed using a software algorithm that updates the motor model equation by comparing the motor output torque current with a reference current. In addition, a simple first-order motor model equation was applied to estimate the output clamping force. The operation time to the maximum clamping force increased within 0.1 seconds compared to the brake pad in its initial condition. The experiment verified that the reference operating time was within 0.5 seconds, and the maximum value of the clamping force was satisfied under the wear condition. The wear compensation method based on the software algorithm in this paper can be performed in the pre-departure test of rolling stock.